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Tytuł:
Metody eksploracji danych i ich zastosowanie
Data mining methods and their applications
Autorzy:
Racka, Katarzyna
Tematy:
data mining
data mining methods
examples of data mining methods applications
data mining software
Pokaż więcej
Wydawca:
Mazowiecka Uczelnia Publiczna w Płocku
Powiązania:
https://bibliotekanauki.pl/articles/446781.pdf  Link otwiera się w nowym oknie
Opis:
Success in the financial market reach those companies that having fast access to data can it properly used. In modern databases and data warehouse are collected vast amounts of information, which man himself is not able to quickly analyze. For this purpose are used the data mining methods that enable the discovery of new knowledge, that is, rules, patterns and relationships in large databases. The aim of this article is to present the data mining methods and their applications. Article is divided into two parts. In the first part of the article explains the concept of data mining and data mining methods are discussed and provides examples of their applications. In the second part of the article presents the companies selling on the Polish market commercial data mining software and examples od free open-source data mining software are discussed.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Methodologies of knowledge discovery from data and data mining methods in mechanical engineering
Autorzy:
Rogalewicz, M.
Sika, R.
Tematy:
knowledge discovery
data mining methods
data mining methodology
Pokaż więcej
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:
https://bibliotekanauki.pl/articles/407431.pdf  Link otwiera się w nowym oknie
Opis:
The paper contains a review of methodologies of a process of knowledge discovery from data and methods of data exploration (Data Mining), which are the most frequently used in mechanical engineering. The methodologies contain various scenarios of data exploring, while DM methods are used in their scope. The paper shows premises for use of DM methods in industry, as well as their advantages and disadvantages. Development of methodologies of knowledge discovery from data is also presented, along with a classification of the most widespread Data Mining methods, divided by type of realized tasks. The paper is summarized by presentation of selected Data Mining applications in mechanical engineering.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Integration of candidate hash trees in concurrent processing of frequent itemset queries using Apriori
Autorzy:
Grudziński, P.
Wojciechowski, M.
Tematy:
data mining
frequent itemset mining
data mining queries
Pokaż więcej
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Powiązania:
https://bibliotekanauki.pl/articles/970835.pdf  Link otwiera się w nowym oknie
Opis:
Frequent itemset mining is often regarded as advanced querying where a user specifies the source dataset and pattern constraints using a given constraint model. In this paper we address the problem of processing batches of frequent itemset queries using the Apriori algorithm. The best solution of this problem proposed so far is Common Counting, which consists in concurrent execution of the queries using Apriori with the integration of scans of the parts of the database shared among the queries. In this paper we propose a new method - Common Candidate Tree, offering a more tight integration of the concurrently processed queries by sharing memory data structures, i.e., candidate hash trees. The experiments show that Common Candidate Tree outperforms Common Counting in terms of execution time. Moreover, thanks to smaller memory consumption, Common Candidate Tree can be applied to larger batches of queries.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analyse the Metrological Data Using Data Mining Technique
Autorzy:
Vanitha, P.
Mayilvaganan, M.
Tematy:
Data Mining
Data Mining Techniques
meteorological data
weather data
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Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Powiązania:
https://bibliotekanauki.pl/articles/1193577.pdf  Link otwiera się w nowym oknie
Opis:
Data Mining is the process of discovering new patterns from large data sets, this technology which is employed in inferring useful knowledge that can be put to use from a vast amount of data, various data mining techniques such as Classification, Prediction, Clustering and Outlier analysis can be used for the purpose. Weather is one of the meteorological data that is rich by important knowledge. Meteorological data mining is a form of data mining concerned with finding hidden patterns inside largely available meteorological data, so that the information retrieved can be transformed into usable knowledge. Sometimes Climate affects the human society in all the possible ways. Knowledge of weather data or climate data in a region is essential for business, society, agriculture and energy applications. The main aim of this paper is to overview on Data mining Process for weather data and to study on weather data using data mining technique like clustering technique. By using this technique we can acquire Weather data and can find the hidden patterns inside the large dataset so as to transfer the retrieved information into usable knowledge for classification and prediction of climate condition.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative Study of Techniques Used in Prediction of Student Performance
Autorzy:
Chauhan, Minakshi
Gupta, Varsha
Tematy:
Classification
Clustering
Data Mining Techniques
Educational Data Mining
Fuzzy Logic
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Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Powiązania:
https://bibliotekanauki.pl/articles/1159721.pdf  Link otwiera się w nowym oknie
Opis:
Providing high quality education is a major concern for higher educational institutions. The quality of education in higher institutions can be assessed by the teaching and learning process. The quality of the teaching learning process depends on the performance of instructor as well as performance of students involved. Analysis and prediction of student performance is key step to identify the poor academic performance. On the basis of prediction, the corrective actions must be taken to improve performance of students and enhance the quality of education system. In this study we surveyed the techniques commonly used to predict the performance of students and also analysed the factors affecting the student academic performance.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Survey on Privacy Preserving Data Mining
Autorzy:
Bharanya, S.
Amudha, P.
Tematy:
Data mining
Frequent pattern mining
Perturbation
Privacy-preserving data mining
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Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Powiązania:
https://bibliotekanauki.pl/articles/1193548.pdf  Link otwiera się w nowym oknie
Opis:
Privacy-preserving data mining has been considered widely because of the wide propagation of sensitive information over internet. A number of algorithmic techniques have been designed for privacy-preserving data mining that includes the state-of-the-art method. Privacy preserving data mining has become progressively popular because it allows sharing of confidential sensitive data for analysis purposes. It is important to maintain a ratio between privacy protection and knowledge discovery. To solve such problems many algorithms are proposed by various authors across the world. The main objective of this paper is to study various Privacy preserving data mining techniques and algorithms used for mining the item sets.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Big Data Mining Approach For Finding Top Rated URL
Autorzy:
Shyam Mohan, J. S.
Shanmugapriya, P.
Kumar, Bhamidipati Vinay Pawan
Tematy:
big data
data mining
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Wydawca:
Społeczna Akademia Nauk w Łodzi
Powiązania:
https://bibliotekanauki.pl/articles/108631.pdf  Link otwiera się w nowym oknie
Opis:
Finding out the widely used URL’s from online shopping sites for any particular category is a difficult task as there are many heterogeneous and multi-dimensional data set which depends on various factors. Traditional data mining methods are limited to homogenous data source, so they fail to sufficiently consider the characteristics of heterogeneous data. This paper presents a consistent Big Data mining search which performs analytics on text data to find the top rated URL’s. Though many heuristic search methods are available, our proposed method solves the problem of searching compared with traditional methods in data mining. The sample results are obtained in optimal time and are compared with other methods which is effective and efficient.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Przegląd i klasyfikacja zastosowań, metod oraz technik eksploracji danych
Data mining review and use’s classification, methods and techniques
Autorzy:
Mirończuk, Marcin
Tematy:
techniki eksploracji danych
zastosowania eksploracji danych
ED
eksploracja danych
metody eksploracji danych
data mining
data mining methods
data mining techniques
data mining classification
data minig review
Pokaż więcej
Wydawca:
Uniwersytet Kazimierza Wielkiego w Bydgoszczy
Powiązania:
https://bibliotekanauki.pl/articles/41204012.pdf  Link otwiera się w nowym oknie
Opis:
Wzrost ilości danych jak i informacji w aktualnych systemach informacyjnych wymusił powstanie nowych procesów oraz technik i metod do ich składowania, przetwarzania oraz analizowania. Do analizy dużych zbiorów danych aktualnie wykorzystuje się osiągnięcia z obszaru analizy statystycznej oraz sztucznej inteligencji (ang. artificial intelligence). Dziedziny te wykorzystane w ramach procesu analizy dużych ilości danych stanowią rdzeń eksploracji danych. Aktualnie eksploracja danych pretenduje do stania się samodzielną metodą naukową wykorzystywaną do rozwiązywania problemów analizy informacji pochodzących m.in. z systemów ich zarządzania. W niniejszym artykule dokonano przeglądu i klasyfikacji zastosowań oraz metod i technik wykorzystywanych podczas procesu eksploracji danych. Dokonano w nim także omówienia aktualnych kierunków rozwoju i elementów składających się na tą młodą stosowaną dziedzinę nauki.
The large quantity of the data and information accumulated into actual information systems and their successive extension extorted the development of new processes, techniques and methods to their storing, processing and analysing. Currently the achievement from the statistical analyses and artificial intelligence area are use to the analysis process of the large data sets. These fields make up the core of data exploration - data mining. Currently the data mining aspires to independent scientific method which one uses to solving problems from range of information analysis comes from the data bases menagments systems. In this article was described review and use's classification, methods and techniques which they are using in the process of the data exploration. In this article also was described actual development direction and described elements which require this young applied discipline of the science.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Combining classifiers for foreign pattern rejectionCombining classifiers for foreign pattern rejection
Autorzy:
Homenda, Władysław
Jastrzębska, Agnieszka
Pedrycz, Witold
Yu, Fusheng
Tematy:
data mining
knowledge engineering
Pokaż więcej
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:
https://bibliotekanauki.pl/articles/1837475.pdf  Link otwiera się w nowym oknie
Opis:
In this paper, we look closely at the issue of contaminated data sets, where apart from legitimate (proper) patterns we encounter erroneous patterns. In a typical scenario, the classification of a contaminated data set is always negatively influenced by garbage patterns (referred to as foreign patterns). Ideally, we would like to remove them from the data set entirely. The paper is devoted to comparison and analysis of three different models capable to perform classification of proper patterns with rejection of foreign patterns. It should be stressed that the studied models are constructed using proper patterns only, and no knowledge about thecharacteristics of foreign patterns is needed. The methods are illustrated with a case study of handwritten digits recognition, but the proposed approach itself is formulated in a general manner. Therefore, it can be applied to different problems. We have distinguished three structures: global, local, and embedded, all capable to eliminate foreign patterns while performing classification of proper patterns at the same time. A comparison of the proposed models shows that the embedded structure provides the best results but at the cost of a relatively high model complexity. The local architecture provides satisfying results and at the same time is relatively simple.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Eksploracja Danych
Data mining
Autorzy:
Zajdel, Dawid
Opis:
Opis wybranych algorytmów eksploracji danych.
A description of chosen data mining algorithms.
Dostawca treści:
Repozytorium Uniwersytetu Jagiellońskiego
Inne
Tytuł:
Fuzzy linguistic data summaries as a human consistent, user adaptable solution to data mining
Raport Badawczy = Research Report ; RB/53/2003
Autorzy:
Zadrożny, Sławomir. Autor
Kacprzyk, Janusz (1947– ). Autor
Wydawca:
Instytut Badań Systemowych. Polska Akademia Nauk
Systems Research Institute. Polish Academy of Sciences
Powiązania:
Raport Badawczy = Research Report
Opis:
Bibliography p. 17-20
Bibliografia s. 17-20
20 stron ; 21 cm
20 pages ; 21 cm
Dostawca treści:
RCIN - Repozytorium Cyfrowe Instytutów Naukowych
Książka
Tytuł:
Parental Mistakes Experienced in Childhood by Girls and Their Needs and Values System as Adult Women
Błędy rodzicielskie doświadczane w dzieciństwie przez dziewczęta a ich potrzeby i system wartości jako dorosłych kobiet
Autorzy:
Szymańska, Agnieszka
Tematy:
parental mistakes
needs
values
data mining algorithms
błędy rodziców
potrzeby
wartości
algorytmy data mining
Pokaż więcej
Wydawca:
Akademia Ignatianum w Krakowie
Powiązania:
https://bibliotekanauki.pl/articles/28763351.pdf  Link otwiera się w nowym oknie
Opis:
Childhood experiences are the foundation on which many personality traits develop. Stressful experiences such as parental mistakes may particularly impact the formation of personality traits. The aim of the current study was to examine how the childhood experiences of parental mistakes, such as aggression, rigor, and so forth, co-occur with the ability to satisfy one’s needs and to one’s value system in adulthood. The study was carried out on a sample of 402 women aged 21 to 50 years. In order to answer the research questions, a cluster analysis using data mining algorithms and Social Network Analysis was performed. The study revealed that women who experienced fewer parental mistakes in childhood displayed greater need fulfillment in adulthood than did women who experienced more parental mistakes. Women differed in their value systems depending on whether they experienced more mistakes from their fathers or mothers. Women who experienced fewer mothers’ mistakes held more values that were focused on others, while women who experienced fewer fathers’ mistakes espoused more self-centered values.
Doświadczenia z dzieciństwa są fundamentem, na którym rozwija się wiele cech osobowości. Stresujące doświadczenia, takie jak błędy rodziców, mogą mocno wpływać na kształtowanie się cech osobowości. Celem niniejszej analizy było zbadanie, w jaki sposób dziecięce doświadczenia błędów rodzicielskich, takich jak agresja, rygor itp., współwystępują ze zdolnością do zaspokajania własnych potrzeb i z systemem wartości w życiu dorosłym. Badanie przeprowadzono na próbie 402 kobiet w wieku od 21 do 50 lat. W celu odpowiedzi na postawione pytania badawcze przeprowadzono analizę skupień z wykorzystaniem algorytmów data mining oraz Analizę Sieci Społecznych. Badanie wykazało, że kobiety, które doświadczyły mniej błędów rodzicielskich w dzieciństwie, wykazywały większe zaspokojenie potrzeb w wieku dorosłym niż kobiety, które doświadczyły więcej błędów rodzicielskich. Kobiety różniły się systemami wartości w zależności od tego, czy więcej błędów popełniały ich ojcowie, czy matki. Kobiety, które doświadczyły mniej błędów popełnionych przez ich matki, wyznawały więcej wartości skoncentrowanych na innych, podczas gdy kobiety, które doświadczyły mniej błędów popełnionych przez ich ojców, wyznawały bardziej egocentryczne wartości.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method for automatic determining of the DBSCAN parameters
Autorzy:
Starczewski, Artur
Goetzen, Piotr
Er, Meng Joo
Tematy:
clustering algorithms
DBSCAN
data mining
Pokaż więcej
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:
https://bibliotekanauki.pl/articles/1837535.pdf  Link otwiera się w nowym oknie
Opis:
Clustering is an attractive technique used in many fields in order to deal with large scale data. Many clustering algorithms have been proposed so far. The most popular algorithms include density-based approaches. These kinds of algorithms can identify clusters of arbitrary shapes in datasets. The most common of them is the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The original DBSCAN algorithm has been widely applied in various applications and has many different modifications. However, there is a fundamental issue of the right choice of its two input parameters, i.e the eps radius and the MinPts density threshold. The choice of these parameters is especially difficult when the density variation within clusters is significant. In this paper, a new method that determines the right values of the parameters for different kinds of clusters is proposed. This method uses detection of sharp distance increases generated by a function which computes a distance between each element of a dataset and its k-th nearest neighbor. Experimental results have been obtained for several different datasets and they confirm a very good performance of the newly proposed method.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A framework for event based modeling and analysis
Autorzy:
Granat, J.
Tematy:
event mining
temporal data mining
telecommunications
Pokaż więcej
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:
https://bibliotekanauki.pl/articles/308870.pdf  Link otwiera się w nowym oknie
Opis:
In this paper we will present a framework for modeling and management of complex systems. There are various approaches for modeling of these systems. One of the approaches is events driven modeling and management of complex system. Such approach is needed in information systems that provide information in real-time. Most of the existing modeling approaches use only information about type of event and the time when an event occurs. However, in the databases we can store and then we can use much richer information about events. This information might be structured as well as unstructured. There are new challenges in algorithms development in case of description of event by various attributes.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Event mining based on observations of the system
Autorzy:
Granat, J.
Tematy:
event mining
temporal data mining
telecommunications
Pokaż więcej
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:
https://bibliotekanauki.pl/articles/309058.pdf  Link otwiera się w nowym oknie
Opis:
Event mining is becoming a challenging area of research. Event in system analysis is not a new concept. It has been used in Petri nets, stochastic modeling, etc. However, there are new opportunities that come from the large amount of data that is stored in various databases. In this paper we will focus on formulating the event mining tasks that consider observations of the system as well as internal and external events.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The symptoms of using Business Intelligence solutions : Poland as viewed against the world trends
Symptomy wykorzystania rozwiązań Business Intelligence : Polska na tle trendów światowych
Autorzy:
Smoląg, Klaudia
Baran, Michał
Opis:
The use of technology that relies on the solutions which may be found within the area of Business Intelligence (BI) is one of the visible factors that direct the companies toward having a recourse to the most advanced, innovative tools to be exploited in the information management. This is consequently the qestion of high significance when viewed from the perspective of possible improvement of the companies’ competitive position in the days referred to as the "information era". In this context there comes to the open the question about the attidude assumed toward the discussed problem by the Polish economic units. The theoretical part of the present contribution provides the characteristic features of the BI solutions and indicates the symptoms that testify to the interest therein. The empirical part is concerned with the research method that relies on the data which reflect the proces of the search for information which is connected with the solutions functioning in the Business Intelligence in the world, including the United States and Poland. This allows for the determining of the domestic specificity in the investigated area.
Wykorzystanie technologii bazujących na rozwiązaniach z zakresu Business Intelligence (BI) jest jednym z widocznych elementów ukierunkowania przedsiębiorstw na sięganie po najbardziej zaawansowane, innowacyjne narzędzia gospodarowania informacją. Jest to zatem zagadnienie o doniosłym znaczeniu z perspektywy możliwości poprawy ich pozycji konkurencyjnej w czasach określanych mianem "ery informacji". Na tym tle rodzi się pytanie o postawę polskich podmiotów gospodarczych w tym względzie. W części teoretycznej scharakteryzowano rozwiązania BI oraz wskazano na symptomy świadczące o zainteresowaniu tymi rozwiązaniami. W części empirycznej sięgnięto po metodę badawczą opartą na porównaniu danych obrazujących proces wyszukiwania informacji związanych z rozwiązaniami z zakresu Business Intelligence na świecie, w Stanach Zjednoczonych, w Polsce. Pozwoliło to określić specyfikę lokalnej, krajowej sytuacji w badanym temacie.
Dostawca treści:
Repozytorium Uniwersytetu Jagiellońskiego
Artykuł
Tytuł:
Modeling preparation for data mining processes
Autorzy:
Eule, T.
Tematy:
data mining
data preparation
KDD process
Pokaż więcej
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:
https://bibliotekanauki.pl/articles/308872.pdf  Link otwiera się w nowym oknie
Opis:
Today many different software tools for decision support exist; the same is true for data mining which can be seen as a particularly challenging sub-area of decision support. Choosing the most suitable tool for a particular industrial data mining application is becoming difficult, especially for industrial decision makers whose expertise is in a different field. This paper provides a conceptual analysis of crucial features of current data mining software tools, by establishing an abstract view on typical processes in data mining. Thus a common terminology is given which simplifies the comparison of tools. Based on this analysis, objective decisions for the application of decision supporting software tools in industrial practice can be made.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using advanced data mining and integration in environmental prediction scenarios
Autorzy:
Habala, O.
Hluchy, L.
Tran, V.
Krammer, P.
Seleng, M.
Tematy:
data mining
data integration
meteorology
hydrology
Pokaż więcej
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Powiązania:
https://bibliotekanauki.pl/articles/305607.pdf  Link otwiera się w nowym oknie
Opis:
We present one of the meteorological and hydrological experiments performed in the FP7 project ADMIRE. It serves as an experimental platform for hydrologists, and we have used it also as a testing platform for a suite of advanced data integration and data mining (DMI) tools, developed within ADMIRE. The idea of ADMIRE is to develop an advanced DMI platform accessible even to users who are not familiar with data mining techniques. To this end, we have designed a novel DMI architecture, supported by a set of software tools, managed by DMI process descriptions written in a specialized high-level DMI language called DISPEL, and controlled via several different user interfaces, each performing a different set of tasks and targeting different user group.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Towards human consistent data driven decision support systems using verbalization of data mining results via linguistic data summaries
Autorzy:
Kacprzyk, J.
Szadrozny, S.
Tematy:
decision support system
data mining
Pokaż więcej
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:
https://bibliotekanauki.pl/articles/200700.pdf  Link otwiera się w nowym oknie
Opis:
We present how the conceptually and numerically simple concept of a fuzzy linguistic database summary can be a very powerful tool for gaining much insight into the essence of data that may be relevant for a business activity. The use of linguistic summaries provides tools for the verbalization of data analysis (mining) results which, in addition to the more commonly used visualization e.g. via a GUI, graphical user interface, can contribute to an increased human consistency and ease of use. The results (knowledge) derived are in a simple, easily comprehensible linguistic form which can be effectively and efficiently employed for supporting decision makers via the data driven decision support system paradigm. Two new relevant aspects of the analysis are also outlined which was first initiated by the authors. First, following Kacprzyk and Zadrożny [1] comments are given on an extremely relevant aspect of scalability of linguistic summarization of data, using their new concept of a conceptual scalability that is crucial for large applications. Second, following Kacprzyk and Zadrożny [2] it is further considered how linguistic data summarization is closely related to some types of solutions used in natural language generation (NLG), which can make it possible to use more and more effective and efficient tools and techniques developed in this another rapidly developing area. An application of a computer retailer is outlined.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
KNAC : an approach for enhancing cluster analysis with background knowledge and explanations
Autorzy:
Nalepa, Grzegorz
Brzegowski, Jakub
Kuk, Michał
Bobek, Szymon
Brzychczy, Edyta
Opis:
Pattern discovery in multidimensional data sets has been the subject of research for decades. There exists a wide spectrum of clustering algorithms that can be used for this purpose. However, their practical applications share a common post-clustering phase, which concerns expert-based interpretation and analysis of the obtained results. We argue that this can be the bottleneck in the process, especially in cases where domain knowledge exists prior to clustering. Such a situation requires not only a proper analysis of automatically discovered clusters but also conformance checking with existing knowledge. In this work, we present Knowledge Augmented Clustering (KNAC). Its main goal is to confront expert-based labelling with automated clustering for the sake of updating and refining the former. Our solution is not restricted to any existing clustering algorithm. Instead, KNAC can serve as an augmentation of an arbitrary clustering algorithm, making the approach robust and a model-agnostic improvement of any state-of-the-art clustering method. We demonstrate the feasibility of our method on artificially, reproducible examples and in a real life use case scenario. In both cases, we achieved better results than classic clustering algorithms without augmentation.
Dostawca treści:
Repozytorium Uniwersytetu Jagiellońskiego
Artykuł
Tytuł:
Augmenting automatic clustering with expert knowledge and explanations
Autorzy:
Bobek, Szymon
Nalepa, Grzegorz
Wydawca:
Springer International Publishing
Opis:
Cluster discovery from highly-dimensional data is a challenging task, that has been studied for years in the fields of data mining and machine learning. Most of them focus on automation of the process, resulting in the clusters that once discovered have to be carefully analyzed to assign semantics for numerical labels. However, it is often the case that such an explicit, symbolic knowledge about possible clusters is available prior to clustering and can be used to enhance the learning process. More importantly, we demonstrate how a machine learning model can be used to refine the expert knowledge and extend it with an aid of explainable AI algorithms. We present our framework on an artificial, reproducible dataset.
Dostawca treści:
Repozytorium Uniwersytetu Jagiellońskiego
Inne
Tytuł:
Analytical intelligence tools for multicriterial diagnostics of CNC machines
Autorzy:
Kuric, I.
Zajačko, I.
Císar, M.
Tematy:
multicriterions diagnostics
analytical intelligence
data mining
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Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Powiązania:
https://bibliotekanauki.pl/articles/957950.pdf  Link otwiera się w nowym oknie
Opis:
Analytical Intelligence is a set of methods and tools for acquisition and transformation of raw data into meaningful and useful information. Multicriterial diagnostics is an approach to obtain a real status of machining process just in time and produce a big pile of raw data. The paper presents a scheme of utilisation of analytical intelligence tools in multicriterial diagnostic of CNC machine tools. It is an effort to obtain a complex perception about all influences represented with measured data on machine precision.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Data mining via fuzzy linguistic data summaries: an implementation of the computing with words and perceptions paradigm
Raport Badawczy = Research Report ; RB/52/2003
Autorzy:
Zadrożny, Sławomir. Autor
Kacprzyk, Janusz (1947– ). Autor
Wydawca:
Instytut Badań Systemowych. Polska Akademia Nauk
Systems Research Institute. Polish Academy of Sciences
Powiązania:
Raport Badawczy = Research Report
Opis:
14 stron ; 21 cm
Bibliografia s. 11-14
Bibliography p. 11-14
We present an approach to fuzzy linguistic summaries of data (bases) in the sense of Yager, i.e., for instance, if we have a (large) database on employees, then if we are interested in, say, age and qualifications, then it may be summarized by, say, “most young employees are well qualified”. We present the derivation of such linguistic summaries in the context of Zadeh’s computing with words and perceptions paradigm, and consider his recent idea of a protoform to define and handle more general forms of summaries. We present an implementation for a small to medium computer retailer, and show how data from the internet can qualitatively enhance the summarization results.
14 pages ; 21 cm
Dostawca treści:
RCIN - Repozytorium Cyfrowe Instytutów Naukowych
Książka
Tytuł:
Performance test on triple heap sort algorithm
Autorzy:
Marszałek, Z.
Tematy:
computer algorithm
data sorting
data mining
computer analysis
Pokaż więcej
Wydawca:
Uniwersytet Warmińsko-Mazurski w Olsztynie
Powiązania:
https://bibliotekanauki.pl/articles/298437.pdf  Link otwiera się w nowym oknie
Opis:
Rapid information search in large data sets is one of the most important issues. Quite often it leads sorting strings stored in different cultures, languages. In this work the author presents a modified triple heap algorithm to sort strings for large data sets. Triple heap algorithm is the subject of research and demonstrating its usefulness in applications.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Data analysis and flow graphs
Autorzy:
Pawlak, Z.
Tematy:
data mining
data independence
flow graph
Bayes' rule
Pokaż więcej
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:
https://bibliotekanauki.pl/articles/308986.pdf  Link otwiera się w nowym oknie
Opis:
In this paper we present a new approach to data analysis based on flow distribution study in a flow network. Branches of the flow graph are interpreted as decision rules, whereas the flow graph is supposed to describe a decision algorithm. We propose to model decision processes as flow graphs and analyze decisions in terms of flow spreading in the graph.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Knowledge mining from data: methodological problems and directions for development
Autorzy:
Kulikowski, J.
Tematy:
data mining
knowledge discovery
data quality
CODATA
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Wydawca:
Politechnika Gdańska
Powiązania:
https://bibliotekanauki.pl/articles/1934003.pdf  Link otwiera się w nowym oknie
Opis:
The development of knowledge engineering and, within its framework, of data mining or knowledge mining from data should result in the characteristics or descriptions of objects, events, processes and/or rules governing them, which should satisfy certain quality criteria: credibility, accuracy, verifiability, topicality, mutual logical consistency, usefulness, etc. Choosing suitable mathematical models of knowledge mining from data ensures satisfying only some of the above criteria. This paper presents, also in the context of the aims of The Committee on Data for Science and Technology (CODATA), more general aspects of knowledge mining and popularization, which require applying the rules that enable or facilitate controlling the quality of data.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Data Mining Process Maturity – Result of Empirical Research
Dojrzałość procesu eksploracji danych – wynik badania empirycznego
Autorzy:
Sliż, Piotr
Tematy:
data mining
data mining process process management process maturity
eksploracja danych proces eksploracji danych
zarządzanie procesami
dojrzałość procesów
Pokaż więcej
Wydawca:
Uniwersytet Warszawski. Wydawnictwo Naukowe Wydziału Zarządzania
Powiązania:
https://bibliotekanauki.pl/articles/526302.pdf  Link otwiera się w nowym oknie
Opis:
The main goal of the article is to present the results of the study relating to the assessment of data mining process maturity on the example of Polish organizations. Several partial objectives were added to the main goal. CT1: To diagnose the current state of knowledge regarding the data-mining process in the discipline of management sciences. Attempts at attaining this objective served to identify the knowledge gap. CT2: To adopt an appropriate theoretical perspective in the form of a theoretical model, enabling the implementation of future research challenges. The first section of the article describes the results of quantitative and qualitative bibliometric analysis. The second section presents the parameters and the definition of the data mining process. Then, the theoretical model used for measuring the maturity of the data mining process is discussed. In the fourth section, the structure of the empirical research conducted and its partial results are outlined. It transpired that the vast majority of the surveyed organizations qualified at the first level of process maturity, defined as a state in which organizations are not aware of the need to identify activities aimed at data mining. Research objectives formulated in the article have been implemented using such research methods as quantitative and qualitative bibliometric analysis, opinion polls and statistical methods.
Celem głównym artykułu było przedstawienie wyników badania oceny dojrzałości procesu eksploracji danych na przykładzie polskich organizacji. Realizacji celu głównego przyporządkowano cele cząstkowe. CT1: Określenie istniejącego stanu wiedzy dotyczącego data-mining process w dyscyplinie nauk o zarządzaniu. Podjęta próba realizacji tego celu służyła identyfikacji luki poznawczej. CT2: Przyjęcie odpowiedniej perspektywy teoretycznej w postaci modelu teoretycznego, umożliwiającego realizację przyszłych wyzwań badawczych. W pierwszej sekcji artykułu opisano wyniki ilościowej i jakościowej analizy bibliometrycznej. Następnie, w sekcji drugiej przedstawiono parametry i definicję procesu eksploracji danych. W sekcji następnej przedstawiono model teoretyczny, wykorzystany do pomiaru dojrzałości procesu eksploracji danych. W sekcji czwartej, w wyniku zrealizowanego postępowania empirycznego scharakteryzowano strukturę badania oraz cząstkowe wyniki. W jego rezultacie stwierdzono, że zdecydowana większość badanych organizacji została zakwalifikowana do pierwszego poziomu dojrzałości procesu, definiowanego jako stan, w którym organizacje nie wykazują świadomości potrzeby identyfikacji działań zmierzających do eksploracji danych. Sformułowane w artykule cele badawcze zostały zrealizowane z wykorzystaniem takich metod badawczych, jak: ilościowa i jakościowa analiza bibliometryczna, sondażowe badanie opinii oraz metody statystyczne.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Mass Violence Detection Using Data Mining Techniques
Autorzy:
Varma, Rishabh
Ahmad, Sartaj
Tematy:
Data mining
Predictive model
Text mining
Tweet analysis
Pokaż więcej
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Powiązania:
https://bibliotekanauki.pl/articles/1159845.pdf  Link otwiera się w nowym oknie
Opis:
The world is now witnessing a tectonic shift in the way in which people react to social and economic impacts such as rise in fossil fuel prices, implication of new rules and regulations, and other situations which directly affect the emotions of a certain group of people. Violence is the most widely used way of expressing anger and discontent for a particular situation which might have occurred. Such actions can cause loss of millions of dollars and precious lives of people who come in way of such protests. These protests are mainly conducted through social media platforms such as twitter as it is not possible to personally communicate to tens of thousand people to accumulate at a certain place, therefore it is extremely important as well as necessary to keep an eye on the social media statuses and updates of people in the times of crisis and heavy tension. This paper aims to collect the tweets of people uploaded on twitter and then process them to find out the location, time and intensity of the mass violence so that the responsible authorities can handle the situation and prevent violence.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Novel System Architecture for an Improved Self-care Solution – Conceptual Design and Key Components
Autorzy:
Santos, Patrick
Ramos, Jorge
Seabra, Eduardo
Castro, José
Tematy:
adaptive interfaces
big data analytics
data mining
user profiling
Pokaż więcej
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:
https://bibliotekanauki.pl/articles/1839314.pdf  Link otwiera się w nowym oknie
Opis:
The high penetration rate that mobile devices enjoy in to day’s society has facilitated the creation of new digital services, with those offered by operators and content providers standing out. However, even this has failed to encourage consumers to express positive opinions on telecommunication services, especially when compared with other sectors. One of the main reasons of the mistrust shown is the low level of quality of customer service provided an area that generates high costs for the operators themselves, due to the high number of people employed at call centers in order to handle the volume of calls received. To face these challenges, operators launched self-care applications in order to provide customers with a tool that would allow them to autonomously manage the services they have subscribed. In this paper, we present an architecture that provides customized information to customers – a solution that is separate from mobile operating systems and communication technologies.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
From business to clinical trials: a systematic review of the literature on fraud detection methods to be used in central statistical monitoring
Autorzy:
Fronc, Maciej
Jakubczyk, Michał
Tematy:
fraud detection
clinical trials
finance
data mining
big data
Pokaż więcej
Wydawca:
Główny Urząd Statystyczny
Powiązania:
https://bibliotekanauki.pl/articles/2176605.pdf  Link otwiera się w nowym oknie
Opis:
Data-driven decisions can be suboptimal when the data are distorted by fraudulent behaviour. Fraud is a common occurrence in finance or other related industries, where large datasets are handled and motivation for financial gain may be high. In order to detect and the prevent fraud, quantitative methods are used. Fraud, however, is also committed in other circumstances, e.g. during clinical trials. The article aims to verify which analytical fraud-detection methods used in finance may be adopted in the field of clinical trials. We systematically reviewed papers published over the last five years in two databases (Scopus and the Web of Science) in the field of economics, finance, management and business in general. We considered a broad scope of data mining techniques including artificial intelligence algorithms. As a result, 37 quantitative methods were identified with the potential of being fit for application in clinical trials. The methods were grouped into three categories: pre-processing techniques, supervised learning and unsupervised learning. Our findings may enhance the future use of fraud-detection methods in clinical trials.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Knowledge discovery from an ERP database in the context of new product development
Autorzy:
Relich University of Zielona Gora, Marcin
Tematy:
knowledge management
project management
data selection
data mining
Pokaż więcej
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Powiązania:
https://bibliotekanauki.pl/articles/431881.pdf  Link otwiera się w nowym oknie
Opis:
This paper is aimed at using an ERP database to identify the variables that have a significant influence on the duration of a project phase. In the paper, some methodologies of the knowledge discovery process are compared and a model of knowledge discovery from an ERP database is proposed. The presented approach is dedicated for the industrial enterprises that use an ERP system to plan and control the development of new products. The example contains four stages of the knowledge discovery process, such as data selection, data transformation, data mining, and the interpretation of patterns. Among data mining techniques, a fuzzy neural system is chosen to seek relationships between data from completed projects and other data stored in an ERP system.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Outlier detection in ocean wave measurements by using unsupervised data mining methods
Autorzy:
Mahmoodi, K.
Ghassemi, H.
Tematy:
ocean wave data
data mining
outlier detection
data correction
Pokaż więcej
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Powiązania:
https://bibliotekanauki.pl/articles/260330.pdf  Link otwiera się w nowym oknie
Opis:
Outliers are considerably inconsistent and exceptional objects in the data set that do not adapt to expected normal condition. An outlier in wave measurements may be due to experimental and configuration errors, technical defects in equipment, variability in the measurement conditions, rare or unknown conditions such as tsunami, windstorm and etc. To improve the accuracy and reliability of an built ocean wave model, or to extract important and valuable information from collected wave data, detecting of outlying observations in wave measurements is very important. In this study, three typical outlier detection algorithms:Box-plot (BP), Local Distance-based Outlier Factor (LDOF), and Local Outlier Factor (LOF) methods are used to detect outliers in significant wave height (Hs) records. The historical wave data are taken from National Data Buoy Center (NDBC). Finally, those data points are considered as outlier identified by at least two methods which are presented and discussed. Then, Hs prediction has been modelled with and without the presence of outliers by using Regression trees (RTs).
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Genre analysis of film reviews created by users of the Filmweb portal
Analiza gatunkowa recenzji filmowych tworzonych przez użytkowników portalu Filmweb
Autorzy:
Patraś, Milena
Opis:
Tematem pracy magisterskiej jest gatunkowość internetowych recenzji filmowych, tworzonych przez użytkowników portalu hobbystycznego Filmweb.pl. Celem pracy magisterskiej jest próba zanalizowania i zbadania recenzji filmowych umieszczanych przez użytkowników na portalu Filmweb.pl. Praca została podzielona na dwie części: teoretyczną i praktyczną. Część teoretyczna stanowi próbę wyjaśnienia takich pojęć jak: historia filmu, teoria filmu, krytyka filmowa oraz recenzja filmowa. Przybliżone zostały również koncepcje gatunkowości, gatunków filmowych czy struktury portalu Filmweb.pl. W części praktycznej analizie poddane zostały recenzje filmowe umieszczane na podstronach filmów portalu Filmweb.pl, z uwzględnieniem 50 recenzji. Przeprowadzono analizę wyników wygenerowanych za pomocą programów MaxQDA oraz Orange Data Mining, a także sformułowano wnioski. Autorka przedstawiła wyniki badań przeprowadzonych na wybranych recenzjach, które są odpowiedzią na przedstawione pytania badawcze.
The topic of this master thesis is genre analysis of online film reviews, posted by users of the website – Filmweb.pl. The purpose of this study is to analyse and research film reviews posted by users on the Filmweb.pl website. The project is divided into two sections. The first section is devoted to the theoretical aspect of the issue, that includes: definitions of concepts such as: film history, film theory, film criticism, film review, genre itself, film genre and the structure of the Filmweb.pl portal. The second section is more about the study itself. It researches the outcome of analysing 50 reviews created by Filmweb users. The analyses were generated using MaxQDA and Orange Data Mining programs. The results of the research have been shown taking into account randomly selected reviews.
Dostawca treści:
Repozytorium Uniwersytetu Jagiellońskiego
Inne
Tytuł:
Frequent itemset discovery algorithms in mining association rules
Algorytmy wyszukiwania zbiorów częstych w eksploracji reguł asocjacyjnych
Autorzy:
Maryański, Krzysztof
Opis:
The following work presents the problem of performance of frequent itemset mining algorithms that can be later used for association rules generation. In the beginning chapters definition and detailed description of association rules is provided. Also, application and interpretation examples are described. Next, selected algorithms for mining frequent itemset and rules generation are described along with examples. An application was created to provide frequent itemset finding (using Apriori, AprioriTiD and Eclat algorithms) and association rules generating functionalities. The application was created in C# using objective programming methods. A set of performance tests were performed using the created program and selected datasets. Test results, along with interpretation and evaluation are presented in last two chapters.
Niniejsza praca przybliża zagadnienie wydajności algorytmów służących do generowania zbiorów częstych z dużych zbiorów danych na potrzeby późniejszego generowania reguł asocjacyjnych. W początkowych rozdziałach zawarto definicję i szczegółowy opis reguł asocjacyjnych. Podano ich zastosowania i przykłady interpretacji. Następnie opisano wybrane algorytmy służące generowaniu zbiorów częstych oraz algorytm generowania reguł asocjacyjnych wraz z przykładami. W ramach pracy stworzono aplikację realizującą wyszukiwanie zbiorów częstych za pomocą wybranych algorytmów (Apriori, AprioriTiD, Eclat) oraz generowanie na tej podstawie reguł i pomiar czasu działania każdego z algorytmów. Implementację przeprowadzono wykorzystując metody programowania obiektowego w języku C#. Przeprowadzono również testy wydajności algorytmów z użyciem stworzonego oprogramowania i wybranych testowych zbiorów danych. W końcowych rozdziałach przedstawiono uzyskane wyniki oraz ich interpretację i ocenę.
Dostawca treści:
Repozytorium Uniwersytetu Jagiellońskiego
Inne
Tytuł:
Management and analytical software for data gathered from HoneyPot system
Autorzy:
Cabaj, K.
Denis, M.
Buda, M.
Tematy:
HoneyPot systems
data mining
monitoring
systemy honeypot
Pokaż więcej
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Powiązania:
https://bibliotekanauki.pl/articles/94827.pdf  Link otwiera się w nowym oknie
Opis:
The paper describes details concerning systems used for analysis and the result of data gathered from two various HoneyPot systems, implemented at Institute of Computer Science. The first system uses data mining techniques for the automatic discovery of interesting patterns in connections directed to the HoneyPot. The second one is responsible for the collection and the initial analysis of attacks dedicated to the Web applications, which nowadays is becoming the most interesting target for cybercriminals. The paper presents results from almost a year of usage, with implemented prototypes, which prove it's practical usefulness. The person performing analysis improves effectiveness by using potentially useful data, which is initially filtered from noise, and automatically generated reports. The usage of data mining techniques allows not only detection of important patterns in rapid manner, but also prevents from overlooking interesting patterns in vast amounts of other irrelevant data.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Ant colony metaphor in a new clustering algorithm
Autorzy:
Boryczka, U.
Tematy:
data mining
cluster analysis
ant clustering algorithm
Pokaż więcej
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Powiązania:
https://bibliotekanauki.pl/articles/969824.pdf  Link otwiera się w nowym oknie
Opis:
Among the many bio-inspired techniques, ant clustering algorithms have received special attention, especially because they still require much investigation to improve performance, stability and other key features that would make such algorithms mature tools for data mining. Clustering with swarm-based algorithms is emerging as an alternative to more conventional clustering methods, such as k-means algorithm. This proposed approach mimics the clustering behavior observed in real ant colonies. As a case study, this paper focuses on the behavior of clustering procedures in this new approach. The proposed algorithm is evaluated on a number of well-known benchmark data sets. Empirical results clearly show that the ant clustering algorithm (ACA) performs well when compared to other techniques.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A novel grid-based clustering algorithm
Autorzy:
Starczewski, Artur
Scherer, Magdalena M.
Książek, Wojciech
Dębski, Maciej
Wang, Lipo
Tematy:
data mining
grid-based clustering
grid structure
Pokaż więcej
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:
https://bibliotekanauki.pl/articles/2031101.pdf  Link otwiera się w nowym oknie
Opis:
Data clustering is an important method used to discover naturally occurring structures in datasets. One of the most popular approaches is the grid-based concept of clustering algorithms. This kind of method is characterized by a fast processing time and it can also discover clusters of arbitrary shapes in datasets. These properties allow these methods to be used in many different applications. Researchers have created many versions of the clustering method using the grid-based approach. However, the key issue is the right choice of the number of grid cells. This paper proposes a novel grid-based algorithm which uses a method for an automatic determining of the number of grid cells. This method is based on the kdist function which computes the distance between each element of a dataset and its kth nearest neighbor. Experimental results have been obtained for several different datasets and they confirm a very good performance of the newly proposed method.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Creating a knowledge database on system dependability and resilience
Autorzy:
Kubacki, M.
Sosnowski, J.
Tematy:
dependability
data mining
event and performance logs
resilience
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Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Powiązania:
https://bibliotekanauki.pl/articles/206779.pdf  Link otwiera się w nowym oknie
Opis:
The paper deals with the problem of creating a knowledge database on system dependability and resilience, created on the basis of available system and application logs. Special to ols to collect and analyse these data from many systems have been developed. Taking into account a wide spectrum of various logs we explore them locally and globally. This allowed for identification of characteristics of normal operation and anomalous behaviour. A lot of attention is paid to the problem of selecting measures to identify symptoms characterising system operation and their usefulness in dependability and resilience evaluation or prediction. The concepts presented are illustrated with experience gained during monitoring of real systems.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Decisions algorithms and flow graphs; a rough set approach
Autorzy:
Pawlak, Z.
Tematy:
rough sets
decision algorithms
flow graphs
data mining
Pokaż więcej
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:
https://bibliotekanauki.pl/articles/307789.pdf  Link otwiera się w nowym oknie
Opis:
This paper concerns some relationship between Bayes' theorem and rough sets. It is revealed that any decision algorithm satisfies Bayes' theorem, without referring to either prior or posterior probabilities inherently associated with classical Bayesian methodology. This leads to a new simple form of this theorem, which results in new algorithms and applications. Besides, it is shown that with every decision algorithm a flow graph can be associated. Bayes' theorem can be viewed as a flow conservation rule of information flow in the graph. Moreover, to every flow graph the Euclidean space can be assigned. Points of the space represent decisions specified by the decision algorithm, and distance between points depicts distance between decisions in the decision algorithm.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Data mining w procesach decyzyjnych
Data mining in decision making processes
Autorzy:
Pałka, D.
Zaskórski, P.
Tematy:
procesy decyzyjne
data mining
OLAP
decision making processes
Pokaż więcej
Wydawca:
Warszawska Wyższa Szkoła Informatyki
Powiązania:
https://bibliotekanauki.pl/articles/91306.pdf  Link otwiera się w nowym oknie
Opis:
W artykule dokonano opisu metod pozyskiwania wiedzy w modelach Data Mining stosowanych do wspo-magania procesu podejmowania decyzji. Głównym założeniem jest próba wykorzystania do tego celu sys-temów klasy OLAP, jako systemów wielowymiarowych i wieloaspektowych drążeń informacji. Proces modelowania takich rozwiązań wymaga strukturalizacji i odniesienia do istniejącej bazy techniczno-technologicznej. Opracowanie prezentuje możliwości budowy modelu dla różnych klas organizacji oraz przedstawia możliwość adaptacji modelu data mining do analizy i zarządzania w procesie podejmowania decyzji. Przydatność modelu widziana może być szczególnie w aspekcie oceny możliwości wspomagania podejmowania decyzji związanych z planowaniem wykorzystania zasobów organizacji rozproszonych do przeciwdziałania skutkom zagrożeń. Nowoczesne koncepcje w zarządzaniu organizacją gospodarczą powinny eksponować platformę Internet, jako platformę ogólnie dostępną do komunikacji z otoczeniem.
The present paper describes methods of knowledge absorption in the Data Mining models in order to support decision making processes. The main assumption is an effort to employ the OLAP systems as multidimensional and multiaspect data in drill down systems. The process of modelling such solutions requires structuring and referring to the existing technical and technological base. The paper presents possible options of model construction for different organisations and describes possible adaptation of the data mining model to the analysis and management of the decision making process. The applicability of the model may be viewed with respect to the analysis of the potential support of decision making with regard to the planning of utilisation of disperse organisations’ resources in order to prevent the hazard effects. Modern concepts of economic organisation management should see the Internet as a widely accessible platform of communication with the environment.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Grade analysis to study ict usage in polish enterprises
Autorzy:
Sieradzki, D.
Urbańczyk, D.
Tematy:
grade correspondence analysis
data mining
GCA
ICT
enterprises
Pokaż więcej
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Powiązania:
https://bibliotekanauki.pl/articles/94725.pdf  Link otwiera się w nowym oknie
Opis:
The aim of this work is to study the structure of information and telecommunications technologies (ICT) usage in Polish enterprises in 2015. In this paper the overrepresentation maps were considered as a tool of data mining. These maps are crated as the results of GCA algorithm. The analysis of data about ICT in Polish enterprises were shown as an example of GCA application. The advantage of the method is the visualization possibility and legibility of the obtained maps. In this article we studied the level of usage of ICT in individual voivodeships, the expenditures for various sectors of ICT for small, medium-size and big enterprises.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Minig rules of concept drift using genetic algorithm
Autorzy:
Vivekanandan, P.
Nedunchezhian, R.
Tematy:
genetic algorithm
CDR-tree algorithm
rules
data mining
Pokaż więcej
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:
https://bibliotekanauki.pl/articles/91705.pdf  Link otwiera się w nowym oknie
Opis:
In a database the data concepts changes over time and this phenomenon is called as concept drift. Rules of concept drift describe how the concept changes and sometimes they are interesting and mining those rules becomes more important. CDR tree algorithm is currently used to identify the rules of concept drift. Building a CDR tree becomes a complex process when the domain values of the attributes get increased. Genetic Algorithms are traditionally used for data mining tasks. In this paper, a Genetic Algorithm based approach is proposed for mining the rules of concept drift, which makes the mining task simpler and accurate when compared with the CDR-tree algorithm.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Об одном новом важном инструменте в области интеллектуального анализа данных
A new important tool in the field of intelligent data analysis
Autorzy:
Dzhun, Joseph
Tematy:
non-classical theory of errors measurement
data mining
Pokaż więcej
Wydawca:
Wyższa Szkoła Gospodarki Euroregionalnej im. Alcide De Gasperi w Józefowie
Powiązania:
https://bibliotekanauki.pl/articles/469842.pdf  Link otwiera się w nowym oknie
Opis:
The new original methods of statistical information processing are used in astrometry and space exploration for many years. It was turned out that these methods have universal character and can be successfully applied in various spheres and it was showed by testing these methods, which were conducted by the department of mathematical modeling of IUEH for 15 years. After testing all these methods were combined in the new “Nonclassical theory of errors measurement” (NTEM) published in 2015. The objective of research: To acquaint the specialists in the field of statistical information mathematical processing and analysis with the objects and opportunities of NTEM and its fundamental regulations because knowledge and usage of which are the most important in our time. As the result significance of the NTEM procedures in the complex of methods that make up the data mining. Methods: The statistical methods which demonstrate adequacy of the methods used by us in practice of observation are considered in the “Nonclassical Theory of Errors Measurement”. Conclusion: NTEM is the new, important and effective tool in the field of mining large amounts of statistical data, particularly in mathematical modeling, its diagnosis and processing of samples, the volume of which
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Apple Tree Yield Analysis Using Data Mining
Autorzy:
Piotrowska, Ewa
Golisz, Ewa
Trajer, Jędrzej
Pietrzycka, Iwona
Wydawca:
Department of Machinery Exploitation and Management of Production Processes, University of Life Sciences in Lublin, Poland
Cytata wydawnicza:
Trajer J., Pietrzycka I., Piotrowska E., Golisz E. 2017. Apple Tree Yield Analysis Using Data Mining. [in:] Lorencowicz E. (ed.), Uziak J. (ed.), Huyghebaert B. (ed.). Farm Machinery and Processes Management in Sustainable Agriculture, 9th International Scientific Symposium. ULS Lublin, p.384-388
Opis:
The paper analyses an orcharding farm that specializes in apple trees production. Based on the data for the period of 2008-2014, the authors analysed the main factors that might have impact on apple yield. A computer system for assessment of apple trees cultivation efficiency that aids in making appropriate decisions allowing for obtaining the highest yield, was proposed. The system was developed using selected Data Mining techniques such as cluster analysis and Kohonen networks. The system may be useful for decision support in sustainable horticulture production, and thus contributes to the development of sustainable agriculture. Although its quality is acceptable it still requires improvement using a bigger dataset.
Dostawca treści:
Repozytorium Centrum Otwartej Nauki
Inne
Książka
Autorzy:
Atzmueller, Martin
Bobek, Szymon
Nalepa, Grzegorz
Kutt, Krzysztof
Opis:
Mining ubiquitous sensing data is important but also challenging, due to many factors, such as heterogeneous large-scale data that is often at various levels of abstraction. This also relates particularly to the important aspects of the explainability and interpretability of the applied models and their results, and thus ultimately to the outcome of the data mining process. With this, in general, the inclusion of domain knowledge leading towards semantic data mining approaches is an emerging and important research direction. This article aims to survey relevant works in these areas, focusing on semantic data mining approaches and methods, but also on selected applications of ubiquitous sensing in some of the most prominent current application areas. Here, we consider in particular: (1) environmental sensing; (2) ubiquitous sensing in industrial applications of artificial intelligence; and (3) social sensing relating to human interactions and the respective individual and collective behaviors. We discuss these in detail and conclude with a summary of this emerging field of research. In addition, we provide an outlook on future directions for semantic data mining in ubiquitous sensing contexts.
Dostawca treści:
Repozytorium Uniwersytetu Jagiellońskiego
Artykuł
Tytuł:
Mobile game evaluation method based on data mining of affective time series
Autorzy:
Drążyk, Dominika
Ochab, Jeremi
Węgrzyn, Paweł
Nalepa, Grzegorz
Witaszczyk, Przemysław
Opis:
Our work is positioned at the intersection of game data science, affective gaming, and the implementation of multimodal body sensors analysis. We propose an original method of evaluating the quality of a class of video games based on the emotional reactions of players. Game developers ask why some games are more profitable (MP games) than others (LP games). An intuitively convincing hypothesis is often put forward: MP games evoke more positive emotions and hence are sustainably engaging. Our main hypothesis is that test players who can clearly distinguish between MP game and LP game in relatively short test sessions are more reliable in scoring games and valuable to keep track of their emotions. From a random group of test players, we selected players with such abilities. We analyzed their affective spectra and obtained a fairly clear confirmation that the selected players showed more positive and less negative emotions in MP games than in LP ones. We can reasonably expect these players to be focused on playing in the test session, and their emotions may really indicate the strengths of MP games over LP games. We present the results of the experimental evaluation of our method conducted with with a leading game company in Poland.
Dostawca treści:
Repozytorium Uniwersytetu Jagiellońskiego
Artykuł
Tytuł:
The concept of business intelligence in the microsoft SQL Server environment
Autorzy:
Szmajduch, M.
Tematy:
business intelligence
e-business
data mining
data warehouse
analytical processing
Pokaż więcej
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Powiązania:
https://bibliotekanauki.pl/articles/95115.pdf  Link otwiera się w nowym oknie
Opis:
Application of supporting business-related decision making processes through the use of information systems is becoming one of the fundamental requirements of the market competition. In this paper we present a survey of Business Intelligence (BI) models which can be implemented in Microsoft SQL Server environment. The survey is a response to the rapid development of BI solutions as they enter new areas of company’s activities, adopting new technologies. Business Intelligence systems have become an integral part of every major company. The aim of this analysis is to present the Microsoft SQL Server capabilities, functionalities and services dedicated for the BI purposes. The overview is provided with simple comprehensive analysis of selected environment components indicating their relevance to the particular company requirements. The summary of the significance of using Microsoft SQL Server software is the review of selected services.
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-50 z 356

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