In this paper we introduce POLAR, a probabilistic objectoriented logical framework for annotation-based information retrieval. In POLAR, the knowledge about digital objects, annot...
Ranking blog posts that express opinions regarding a given topic should serve a critical function in helping users. We explored a couple of methods for opinion retrieval in the fr...
The classical probabilistic models attempt to capture the Ad hoc information retrieval problem within a rigorous probabilistic framework. It has long been recognized that the prim...
The probability that a term appears in relevant documents ( ) is a fundamental quantity in several probabilistic retrieval models, however it is difficult to estimate without rele...
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...