Understanding query intent is essential to generating appropriate rankings for users. Existing methods have provided customized rankings to answer queries with different intent. W...
We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...
Abstract. We present a framework that assesses relevance with respect to several relevance criteria, by combining the query-dependent and query-independent evidence indicating thes...
We describe a machine learning approach for predicting sponsored search ad relevance. Our baseline model incorporates basic features of text overlap and we then extend the model t...
Dustin Hillard, Stefan Schroedl, Eren Manavoglu, H...
Web data extraction is concerned, among other things, with routine data accessing and downloading from continuously-updated dynamic Web pages. There is a relevant trade-off between...