End-user interactive machine learning is a promising tool for enhancing human productivity and capabilities with large unstructured data sets. Recent work has shown that we can cr...
Saleema Amershi, James Fogarty, Ashish Kapoor, Des...
Web textual advertising can be interpreted as a search problem over the corpus of ads available for display in a particular context. In contrast to conventional information retrie...
Andrei Z. Broder, Massimiliano Ciaramita, Marcus F...
In constrained data mining, users can specify constraints that can be used to prune the search space to avoid mining uninteresting knowledge. Since it is difficult to determine th...
Gao Cong, Beng Chin Ooi, Kian-Lee Tan, Anthony K. ...
This paper develops and analyzes distributed search techniques for use in a peer-to-peer (P2P) network-based Information Retrieval (IR) system. In the absence of a centralized med...
Haizheng Zhang, W. Bruce Croft, Brian Neil Levine,...
This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...