We introduce in this paper the family of information-based models for ad hoc information retrieval. These models draw their inspiration from a long-standing hypothesis in IR, name...
In this paper we explore the use of parsimonious language models for web retrieval. These models are smaller thus more efficient than the standard language models and are therefor...
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
We introduce the Ranked Feature Fusion framework for information retrieval system design. Typical information retrieval formalisms such as the vector space model, the bestmatch mo...
A statistical correlation model for image retrieval is proposed. This model captures the semantic relationships among images in a database from simple statistics of userprovided r...