Temat: data - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Big Data = Clear + Dirty + Dark Data
Autorzy:: Migdał-Najman, Kamila
Najman, Krzysztof
Tematy:: Big Data
Clear Data
Dirty Data
Dark Data; Pokaż więcej
Data publikacji:: 2017
Powiązania:: https://bibliotekanauki.pl/articles/582881.pdf Link otwiera się w nowym oknie
Źródło:: Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu; 2017, 469; 131-139
1899-3192
Pojawia się w:: Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
Opis:: Rozwój techniki teleinformacyjnej, Internetu i informatyki przy jednoczesnym spadku jednostkowych kosztów gromadzenia i przechowywania danych powoduje istotne ilościowe i jakościowe zmiany w podejściu zarówno do samych danych, jak i możliwości ich analizy. Ten coraz bardziej gęsty, ciągły i niestrukturyzowany strumień danych, nazywany Big Data, wywołuje współcześnie wiele emocji. Z jednej strony brak odpowiedniej ilości danych był zawsze wyzwaniem dla metod wnioskowania statystycznego i jednym z bodźców ich rozwoju. Jednak z drugiej strony, w dużych liczebnościach prób zawarte są liczne zagrożenia dla wiarygodności wnioskowania. W zbiorach takich, poza danymi o odpowiedniej jakości (Clear Data), znaczny udział mają dane nieprawdziwe, nieaktualne, zaszumione, często wielokrotnie zduplikowane, niekompletne lub błędne (Dirty Data), a także dane, o których jakości czy użyteczności nic nie wiadomo (Dark Data). Celem prezentowanych badań jest krytyczne przedstawienie struktury jakościowej zbioru Big Data.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Analyse the Metrological Data Using Data Mining Technique
Autorzy:: Vanitha, P.
Mayilvaganan, M.
Tematy:: Data Mining
Data Mining Techniques
meteorological data
weather data; Pokaż więcej
Data publikacji:: 2016
Powiązania:: https://bibliotekanauki.pl/articles/1193577.pdf Link otwiera się w nowym oknie
Źródło:: World Scientific News; 2016, 41; 239-246
2392-2192
Pojawia się w:: World Scientific News
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

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Skocz do pozycji: 3.

Tytuł:: Prawne i etyczne ograniczenia wykorzystania danych biometrycznych w Unii Europejskiej i w Polsce
Autorzy:: Porzeżyński, Marek
Tematy:: data
personal data
biometric data
information
new technologies; Pokaż więcej
Data publikacji:: 2023-04-24
Powiązania:: https://bibliotekanauki.pl/articles/48899284.pdf Link otwiera się w nowym oknie
Źródło:: Studia Iuridica; 2022, 94; 317-337
0137-4346
Pojawia się w:: Studia Iuridica
Opis:: Technological development has never been so rapid as today. Due to the emerging technologies, their users gain considerable advantages in their everyday life. At the same time, such facilitation has an effect on our privacy and entails a risk of a wide range of information becoming easily available to unauthorised entities or persons. However, the risk is even greater when the scope of data required to get access to a particular solution becomes broader. In some cases, the amount of data requested from the user seems largely redundant. In this context, it is worth mentioning, for example, biometric data increasingly used for authentication of the user wishing to access applications by means of fingerprint scanning or facial recognition. The question is whether this is really necessary in all situations, or possibly in some circumstances the use of biometrics may pose a greater threat to privacy than to the information protected this way. The author presents the current restrictions on the use of biometric data, along with their assessment.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Detection and quantification of self- similarity in data traffic for prediction of performance of marine data file transfer
Autorzy:: Konorski, J.
Tematy:: marine data
data traffic; Pokaż więcej
Data publikacji:: 1999
Powiązania:: https://bibliotekanauki.pl/articles/1920405.pdf Link otwiera się w nowym oknie
Źródło:: Biuletyn Instytutu Morskiego w Gdańsku; 1999, 26, 2; 29-48
1230-7424
2450-5536
Pojawia się w:: Biuletyn Instytutu Morskiego w Gdańsku
Opis:: The time-sensitivity of large marine data files over a communication network necessitates accurate simulative prediction of the file transfer performance. Careful data traffic modelling is required to fit the actual traffic characteristics for subsequent generation of synthetic traffic traces and feeding them into a simulation model. Classical models have recently proved inadequate due to the discovery of self-similarity (fractal behaviour) in data traffic. This paper attempts to systematise the mathematical background of self-similarity and the ways it manifests itself in stochastic processes modelling data traffic. Relevance of self-similarity to traffic description and measurements is discussed. Results of a research effort at the Department of Marine Electronics of the Maritime Institute in Gdansk are described, which focus on the development of a software tool for detection and quantification of self- similarity in observed or synthetically generated data traffic.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Data and Task Scheduling in Distributed Computing Environments
Autorzy:: Szmajduch, M.
Tematy:: data cloud
data grid
data processing
data scheduling
ETC Matrix; Pokaż więcej
Data publikacji:: 2014
Powiązania:: https://bibliotekanauki.pl/articles/309172.pdf Link otwiera się w nowym oknie
Źródło:: Journal of Telecommunications and Information Technology; 2014, 4; 71-78
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Opis:: Data-aware scheduling in today’s large-scale heterogeneous environments has become a major research and engineering issue. Data Grids (DGs), Data Clouds (DCs) and Data Centers are designed for supporting the processing and analysis of massive data, which can be generated by distributed users, devices and computing centers. Data scheduling must be considered jointly with the application scheduling process. It generates a wide family of global optimization problems with the new scheduling criteria including data transmission time, data access and processing times, reliability of the data servers, security in the data processing and data access processes. In this paper, a new version of the Expected Time to Compute Matrix (ETC Matrix) model is defined for independent batch scheduling in physical network in DG and DC environments. In this model, the completion times of the computing nodes are estimated based on the standard ETC Matrix and data transmission times. The proposed model has been empirically evaluated on the static grid scheduling benchmark by using the simple genetic-based schedulers. A simple comparison of the achieved results for two basic scheduling metrics, namely makespan and average flowtime, with the results generated in the case of ignoring the data scheduling phase show the significant impact of the data processing model on the schedule execution times.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Data Fixing Algorithm in Radiosonde Monitoring Process
Autorzy:: Szuster, P.
Tematy:: aerology
data ﬁxing
data fusion
meteorological data
monitoring
radiosondes; Pokaż więcej
Data publikacji:: 2017
Powiązania:: https://bibliotekanauki.pl/articles/308014.pdf Link otwiera się w nowym oknie
Źródło:: Journal of Telecommunications and Information Technology; 2017, 1; 81-88
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Opis:: Earth surface monitoring can give information that may be used in complex analysis of the air conditions, temperature, humidity etc. Data from a vertical profile of the atmosphere is also essential for accurate thunderstorm forecasting. That data is collected by radiosondes – telemetry instruments carried into the atmosphere usually by balloons. Sometimes, due to the hostile conditions of upper troposphere, incorrect data can be generated by radiosonde sensors. In this paper, a new algorithm is developed for fixing the incorrect data, i.e. missing or out of specific range values. The proposed algorithm was tested both on benchmarks and real data generated by radiosondes. About 70% of significantly damaged test data volume was recovered. Up to 100% of real data was fixed.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Problems with rendering the information accessible and presenting the information in publicly accessible databases
Autorzy:: Wichorowski, M.
Węsławski, J. M.
Wyrwiński, J
Tematy:: data acquisition
databases
data collections
data storage
inventories
legislation
oceanographic data; Pokaż więcej
Data publikacji:: 2000
Powiązania:: https://bibliotekanauki.pl/articles/1941703.pdf Link otwiera się w nowym oknie
Źródło:: TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2000, 4, 1; 121-126
1428-6394
Pojawia się w:: TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Opis:: Based on the experience acquired from working on the Regional Oceanographic Database (ROD) at the IOPAS in Sopot and from cooperation with similar scientific facilities, a general review of problems with the security of data ownership, copyrights, rendering the scientific information accessible, propagating it and differences in the access to data in European Union and Poland was presented. A system for accessing processed data, educational data and source information was proposed.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

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
Data publikacji:: 2015
Powiązania:: https://bibliotekanauki.pl/articles/446781.pdf Link otwiera się w nowym oknie
Źródło:: Zeszyty Naukowe PWSZ w Płocku. Nauki Ekonomiczne; 2015, 1(21); 143-150
1644-888X
Pojawia się w:: Zeszyty Naukowe PWSZ w Płocku. Nauki Ekonomiczne
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

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Skocz do pozycji: 9.

Tytuł:: Issues of personal data management in organizations – GDPR compliance level analysis
Autorzy:: Kucęba, Robert
Chmielarz, Grzegorz
Tematy:: personal data
personal data protection
personal data security breaches
GDPR; Pokaż więcej
Data publikacji:: 2018
Powiązania:: https://bibliotekanauki.pl/articles/432163.pdf Link otwiera się w nowym oknie
Źródło:: Informatyka Ekonomiczna; 2018, 1(47); 58-71
1507-3858
Pojawia się w:: Informatyka Ekonomiczna
Opis:: The paper presents the issues of information and personal data security management in organizations. The authors include in it an analysis of breaches to personal data security in organizations as a vital factor that conditions the necessity to improve the previously applied solutions in this area. Additionally, the paper contains analyses concerning the preparation level of organizations to ensure compliance with the General Data Protection Regulation (GDPR) which is coming into force. The paper constitutes a cognitive query in the scope of the subject matter defined in its title
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

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; Pokaż więcej
Data publikacji:: 2015
Powiązania:: https://bibliotekanauki.pl/articles/108631.pdf Link otwiera się w nowym oknie
Źródło:: Journal of Applied Computer Science Methods; 2015, 7 No. 1; 17-32
1689-9636
Pojawia się w:: Journal of Applied Computer Science Methods
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

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