Verylarge databases with skewedclass distributions and non-unlformcost per error are not uncommonin real-world data mining tasks. Wedevised a multi-classifier meta-learningapproac...
In many criminal cases, forensically collected data contain valuable information about a suspect’s social networks. An investigator often has to manually extract information fro...
Rabeah Al-Zaidy, Benjamin C. M. Fung, Amr M. Youss...
Data mining focuses on the development of methods and algorithms for such tasks as classification, clustering, rule induction, and discovery of associations. In the database fiel...
We introduce the new paradigm of Change Mining as data mining over a volatile, evolving world with the objective of understanding change. While there is much work on incremental m...
A lack of power and extensibility in their query languages has seriously limited the generality of DBMSs and hampered their ability to support data mining applications. Thus, ther...