Data clustering methods have many applications in the area of data mining. Traditional clustering algorithms deal with quantitative or categorical data points. However, there exist...
Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzew...
Information extraction (IE) from semi-structured Web documents is a critical issue for information integration systems on the Internet. Previous work in wrapper induction aim to so...
Inclusion of domain knowledge in a process of knowledge discovery in databases is a complex but very important part of successful knowledge discovery solutions. In real-life data m...
Knowledge is a vital component for organisational growth and data mining provides the technological basis for automated knowledge elicitation from data sources. The emergence of Ap...
Shonali Krishnaswamy, Seng Wai Loke, Arkady B. Zas...
Advances in image acquisition and storage technology have led to tremendous growth in significantly large and detailed image databases. These images, if analyzed, can reveal usefu...
: Experience Management (EM) is an area that is increasingly gaining importance. Its roots lie in Experimental Software Engineering ("Experience Factory"), in Artificial ...
Abstract. We present a simple Data Mining Logic (DML) that can express common data mining tasks, like “Find Boolean association rules” or “Find inclusion dependencies.” At ...
Data mining has been defined as the non- trivial extraction of implicit, previously unknown and potentially useful information from data. Association mining is one of the important...
Peter Bollmann-Sdorra, Aladdin Hafez, Vijay V. Rag...