Renáta Iváncsy

Budapest University of Technology and Economics · Department of Automation and Applied Informatics

Knowledge discovery is an iterative and interactive process where the appropriate solution for a given problem can be found only with big effort. There are several algorithms for each piece of problems that can be used for discovering hidden relationships in data. Choosing the best feasible method is not a trivial process. It is advisable to apply...

Clustering means grouping target objects into different clusters in such a way, that each cluster contains similar objects and the objects in different clusters are dissimilar in a ceratin way. The main question of clustering is how to define the similarity and dissimilarity of the objects, and how to verify that the resulting clusters are good eno...

The expansion of the World Wide Web has resulted in a large amount of data that is now freely available for user access. The data have to be managed and organized in such a way that the user can access them efficiently. For this reason the application of data mining techniques on the Web is now the focus of an increasing number of researchers. One...

Web content providers need to obtain precise information about the visits on their site in order to improve their services. They often contract with independent third party auditing companies. These companies collect an enormous amount of multi-dimensional data that is quite difficult to visualize. This paper describes four visualization techniques...

Clustering is the process of grouping objects together in such a way that the objects belonging to the same group are similar and those belonging to different groups are dissimilar. Clustering technique can be used in many applications for example biological, financial applications and many more. One of these application types is Web clustering whe...

Evolutionary optimization algorithms contain, due to their heuristic inspiration, many heuristic parameters, which need to be empirically tuned for the algorithm to work most properly. This paper deals with tuning those parameters in situations when ...

Frequent itemset discovering is a highly researched area in the field of data mining. The algorithms dealing with this problem have several advantages and disadvantages regarding their time complexity, I/O cost and memory requirement. There are algorithms that have moderate memory usage but high I/O cost, thus the execution time of them is high; su...

Frequent pattern mining is a heavily researched area in the field of data miningwith wide range of applications. One of them is to use frequent pattern discovery methodsin Web log data. Discovering hidden information from Web log data is called Web usagemining. The aim of discovering frequent patterns in Web log data is to obtain informationabout t...

Frequent pattern mining as part of the data mining process can be used in many applications. The type of the patterns can be various regarding the problem to be solved. In several cases the problem can be modeled with graphs only, thus methods are needed which can discover such patterns from large databases. Trees are special graphs where one path...

Sequential pattern mining is a heavily researched area in the field of data mining with wide variety of applications. The task of discovering frequent sequences is challenging, because the algorithm needs to process a combinatorially explosive number of possible sequences. Most of the methods dealing with the sequential pattern mining problem are b...

Mining frequent patterns in large transactional databases is a highly researched area in the field of data mining. The different existing frequent pattern discovering algorithms suffer from various problems re- garding the computational and I/O cost, and memory requirements when mining large amount of data. In this paper a novel approach is introdu...

Clustering is one of the most important research areas in the field of data mining. Clustering means creating groups of objects based on their features in such a way that the objects belonging to the same groups are similar and those belonging in different groups are dissimilar. In this paper the most representative algorithms are described and cat...

With the increasing importance on multimedia applications, the production of multimedia information resulted in a large amount of image and video data which are stored in multimedia databases. Thus image indexing has become important since ever huger databases exist to store this kind of data. The effectiveness of the image retrieval can be enhance...

Voice Over IP (VoIP for short) on wired line networks has gained significant attention in the past few years as the bandwidth of the internet accesses of a custom user is increasing continuously. The expansion of using the mobile environment induces an effort for integrating mobile communication with VoIP. However, integrating mobile environment wi...

This paper describes an enhanced cookie-based method for counting the visitors of web sites by using a web log processing system that aims to cope with the ambitious goal of creating countrywide statistics about the browsing practices of real human individuals. The focus is put on describing a new more efficient way of detecting human beings behind...