Data mining is an interactive and iterative process. Users issue series of similar queries until they receive satisfying results, yet currently available data mining systems do not...
Most of the complexity of common data mining tasks is due to the unknown amount of information contained in the data being mined. The more patterns and correlations are contained ...
Paolo Palmerini, Salvatore Orlando, Raffaele Pereg...
Nowadays, decision support systems are evolving in order to handle complex data. Some recent works have shown the interest of combining on-line analysis processing (OLAP) and data...
Riadh Ben Messaoud, Omar Boussaid, Sabine Rabas&ea...
To enable information integration, schema matching is a critical step for discovering semantic correspondences of attributes across heterogeneous sources. As a new attempt, this p...
Integrating data from multiple sources has been a longstanding challenge in the database community. Techniques such as privacy-preserving data mining promises privacy, but assume ...
Chris Clifton, Murat Kantarcioglu, AnHai Doan, Gun...
Privacy concerns have become an important issue in data mining. A popular way to preserve privacy is to randomize the dataset to be mined in a systematic way and mine the randomiz...
Record linkage, the problem of determining when two records refer to the same entity, has applications for both data cleaning (deduplication) and for integrating data from multipl...
Data mining has been widely recognized as a powerful tool to explore added value from large-scale databases. One of data mining techniques, generalized association rule mining wit...
Cluster analysis is a common approach to pattern discovery in spatial databases. While many clustering techniques have been developed, it is still challenging to discover implicit...