Automatically clustering web pages into semantic groups promises improved search and browsing on the web. In this paper, we demonstrate how user-generated tags from largescale soc...
Daniel Ramage, Paul Heymann, Christopher D. Mannin...
Understanding query intent is essential to generating appropriate rankings for users. Existing methods have provided customized rankings to answer queries with different intent. W...
The Multimedia and Information Systems group at the Knowledge Media Institute of the Open University participated in the Expert Search and Document Search tasks of the Enterprise ...
: We describe our participation in the TREC 2004 Web and Terabyte tracks. For the web track, we employ mixture language models based on document full-text, incoming anchortext, and...
Traditionally, search engines have ignored the reading difficulty of documents and the reading proficiency of users in computing a document ranking. This is one reason why Web se...
Kevyn Collins-Thompson, Paul N. Bennett, Ryen W. W...