Many of the recently proposed algorithms for learning feature-based ranking functions are based on the pairwise preference framework, in which instead of taking documents in isola...
Vitor R. Carvalho, Jonathan L. Elsas, William W. C...
We investigate the idea of finding semantically related search engine queries based on their temporal correlation; in other words, we infer that two queries are related if their p...
The wealth of information available on the web makes it an attractive resource for seeking quick answers. While web-based question answering becomes an emerging topic in recent ye...
Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Eff...
Document clustering has long been an important problem in information retrieval. In this paper, we present a new clustering algorithm ASI1, which uses explicitly modeling of the s...