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Wyświetlanie 1-15 z 281
Tytuł:
Metody eksploracji danych i ich zastosowanie
Data mining methods and their applications
Autorzy:
Racka, Katarzyna
Powiązania:
https://bibliotekanauki.pl/articles/446781.pdf
Data publikacji:
2015
Wydawca:
Mazowiecka Uczelnia Publiczna w Płocku
Tematy:
data mining
data mining methods
examples of data mining methods applications
data mining software
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.
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
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.
Powiązania:
https://bibliotekanauki.pl/articles/970835.pdf
Data publikacji:
2009
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
data mining
frequent itemset mining
data mining queries
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.
Źródło:
Control and Cybernetics; 2009, 38, 1; 47-65
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analyse the Metrological Data Using Data Mining Technique
Autorzy:
Vanitha, P.
Mayilvaganan, M.
Powiązania:
https://bibliotekanauki.pl/articles/1193577.pdf
Data publikacji:
2016
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Data Mining
Data Mining Techniques
meteorological data
weather data
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.
Źródło:
World Scientific News; 2016, 41; 239-246
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Methodologies of knowledge discovery from data and data mining methods in mechanical engineering
Autorzy:
Rogalewicz, M.
Sika, R.
Powiązania:
https://bibliotekanauki.pl/articles/407431.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
knowledge discovery
data mining methods
data mining methodology
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.
Źródło:
Management and Production Engineering Review; 2016, 7, 4; 97-108
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Survey on Privacy Preserving Data Mining
Autorzy:
Bharanya, S.
Amudha, P.
Powiązania:
https://bibliotekanauki.pl/articles/1193548.pdf
Data publikacji:
2016
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Data mining
Frequent pattern mining
Perturbation
Privacy-preserving data mining
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.
Źródło:
World Scientific News; 2016, 41; 68-75
2392-2192
Pojawia się w:
World Scientific News
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
Powiązania:
https://bibliotekanauki.pl/articles/108631.pdf
Data publikacji:
2015
Wydawca:
Społeczna Akademia Nauk w Łodzi
Tematy:
big data
data mining
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.
Źródło:
Journal of Applied Computer Science Methods; 2015, 7 No. 1; 17-32
1689-9636
Pojawia się w:
Journal of Applied Computer Science Methods
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative Study of Techniques Used in Prediction of Student Performance
Autorzy:
Chauhan, Minakshi
Gupta, Varsha
Powiązania:
https://bibliotekanauki.pl/articles/1159721.pdf
Data publikacji:
2018
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Classification
Clustering
Data Mining Techniques
Educational Data Mining
Fuzzy Logic
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.
Źródło:
World Scientific News; 2018, 113; 185-193
2392-2192
Pojawia się w:
World Scientific News
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
Powiązania:
https://bibliotekanauki.pl/articles/1837475.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
data mining
knowledge engineering
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.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 2; 75-94
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A framework for event based modeling and analysis
Autorzy:
Granat, J.
Powiązania:
https://bibliotekanauki.pl/articles/308870.pdf
Data publikacji:
2006
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
event mining
temporal data mining
telecommunications
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.
Źródło:
Journal of Telecommunications and Information Technology; 2006, 4; 88-90
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Event mining based on observations of the system
Autorzy:
Granat, J.
Powiązania:
https://bibliotekanauki.pl/articles/309058.pdf
Data publikacji:
2005
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
event mining
temporal data mining
telecommunications
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.
Źródło:
Journal of Telecommunications and Information Technology; 2005, 3; 87-90
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modeling preparation for data mining processes
Autorzy:
Eule, T.
Powiązania:
https://bibliotekanauki.pl/articles/308872.pdf
Data publikacji:
2006
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
data mining
data preparation
KDD process
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.
Źródło:
Journal of Telecommunications and Information Technology; 2006, 4; 81-87
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
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.
Powiązania:
https://bibliotekanauki.pl/articles/305607.pdf
Data publikacji:
2012
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
data mining
data integration
meteorology
hydrology
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.
Źródło:
Computer Science; 2012, 13 (1); 5-16
1508-2806
2300-7036
Pojawia się w:
Computer Science
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.
Powiązania:
https://bibliotekanauki.pl/articles/200700.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
decision support system
data mining
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.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2010, 58, 3; 359-370
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method for automatic determining of the DBSCAN parameters
Autorzy:
Starczewski, Artur
Goetzen, Piotr
Er, Meng Joo
Powiązania:
https://bibliotekanauki.pl/articles/1837535.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
clustering algorithms
DBSCAN
data mining
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.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 3; 209-221
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Knowledge mining from data: methodological problems and directions for development
Autorzy:
Kulikowski, J.
Powiązania:
https://bibliotekanauki.pl/articles/1934003.pdf
Data publikacji:
2011
Wydawca:
Politechnika Gdańska
Tematy:
data mining
knowledge discovery
data quality
CODATA
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.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2011, 15, 2; 227-233
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 281

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