High-dimensional mixed-attribute data clustering has become an important research direction in data mining area. Because of the advantages of the information technology, data coll...
Nowadays, due to the lack of face-to-face contact, distance course instructors have real difficulties knowing who their students are, how their students behave in the virtual cour...
This survey paper categorises, compares, and summarises from almost all published technical and review articles in automated fraud detection within the last 10 years. It defines t...
Clifton Phua, Vincent C. S. Lee, Kate Smith-Miles,...
Lots of work has already been published on developing applications for schema or ontology matching. Most of these approaches do not take the usability aspect into account. This pa...
Data mining can extract important knowledge from large data collections - but sometimes these collections are split among various parties. Privacy concerns may prevent the parties...
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
This study compares five well-known association rule algorithms using three real-world datasets and an artificial dataset. The experimental results confirm the performance improve...
REVI-MINER is a KDD-environment which supports the detection and analysis of deviations in warranty and goodwill cost statements. The system was developed within the framework of ...
Edgar Hotz, Udo Grimmer, W. Heuser, Gholamreza Nak...
This paper studies the problem of categorical data clustering, especially for transactional data characterized by high dimensionality and large volume. Starting from a heuristic m...
This panel will discuss possible exciting and motivating Grand Challenge problems for Data Mining, focusing on bioinformatics, multimedia mining, link mining, text mining, and web...
Gregory Piatetsky-Shapiro, Robert Grossman, Chaban...