We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possibl...
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andr...
Language Modeling (LM) has been successfully applied to Information Retrieval (IR). However, most of the existing LM approaches only rely on term occurrences in documents, queries...
Jing Bai, Dawei Song, Peter Bruza, Jian-Yun Nie, G...
We present methods for improving text search retrieval of visual multimedia content by applying a set of visual models of semantic concepts from a lexicon of concepts deemed relev...
Alexander Haubold, Apostol Natsev, Milind R. Napha...
Pseudo-relevance feedback (PRF) improves search quality by expanding the query using terms from high-ranking documents from an initial retrieval. Although PRF can often result in ...
Marc-Allen Cartright, James Allan, Victor Lavrenko...
A large part of the data on the World Wide Web is hidden behind form-like interfaces. These interfaces interact with a hidden backend database to provide answers to user queries. ...