Accurately and effectively detecting the locations where search queries are truly about has huge potential impact on increasing search relevance. In this paper, we define a search...
Lee Wang, Chuang Wang, Xing Xie, Josh Forman, Yans...
We propose a fully decentralized collaborative filtering approach that is self-organizing and operates in a distributed way. The relevances between downloading files (items) are...
Jun Wang, Marcel J. T. Reinders, Reginald L. Lagen...
Electronic mail poses a number of unusual challenges for the design of information retrieval systems and test collections, including informal expression, conversational structure,...
When investigating alternative estimates for term discriminativeness, we discovered that relevance information and idf are much closer related than formulated in classical literat...
We formulate and study search algorithms that consider a user’s prior interactions with a wide variety of content to personalize that user’s current Web search. Rather than re...
This paper presents an algorithm for unsupervised noun sense induction, based on clustering of Web search results. The algorithm does not utilize labeled training instances or any...
Goldee Udani, Shachi Dave, Anthony Davis, Tim Sibl...
We study the problem of offering publish/subscribe functionality on top of structured overlay networks using data models and languages from IR. We show how to achieve this by ext...
Previous research into the efficiency of text retrieval systems has dealt primarily with methods that consider inverted lists in sequence; these methods are known as term-at-a-tim...