We apply a well-known Bayesian probabilistic model to textual information retrieval: the classification of documents based on their relevance to a query. This model was previously...
This paper addresses the issue of devising a new document prior for the language modeling (LM) approach for Information Retrieval. The prior is based on term statistics, derived in...
Prior work has shown that combining results of various retrieval approaches and query representations can improve search effectiveness. Today, many meta-search engines exist which...
M. Catherine McCabe, Abdur Chowdhury, David A. Gro...
We analyse the kinematics of probabilistic term weights at retrieval time for di erent Information Retrieval models. We present four models based on di erent notions of probabilis...
We present a generative model for determining the information content of a message without analyzing the message content. Such a tool is useful for automated analysis of the vast ...
Yingjie Zhou, Malik Magdon-Ismail, William A. Wall...