The collective contributions of billions of users across the globe each day result in an ever-changing web. In verticals like news and real-time search, recency is an obvious sign...
Abstract. We present a new learning to rank framework for estimating context-sensitive term weights without use of feedback. Specifically, knowledge of effective term weights on ...
An expert finding is a very common task among enterprise search activities, while its usual retrieval performance is far from the quality of the Web search. Query modeling helps t...
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions for different search domains, ...
Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, La...
In this paper we address the problem of unsupervised Web data extraction. We show that unsupervised Web data extraction becomes feasible when supposing pages that are made up of r...