Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Predicting items a user would like on the basis of other users' ratings for these items has become a well-established strategy adopted by many recommendation services on the ...
This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
Tasks recognizing named entities such as products, people names, or locations from documents have recently received significant attention in the literature. Many solutions to thes...
Web search engines are facing formidable performance challenges as they need to process thousands of queries per second over billions of documents. To deal with this heavy workloa...