In this paper we propose a model for relevance feedback. Our model combines evidence from user's relevance assessments with algorithms describing how words are used within do...
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
We demonstrate that regularization can improve feedback in a language modeling framework. Categories and Subject Descriptors: H.3.3 Information Search and Retrieval: Relevance Fee...
In this paper, we propose a joint probabilistic topic model for simultaneously modeling the contents of multi-typed objects of a heterogeneous information network. The intuition b...
We consider blog feed search: identifying relevant blogs for a given topic. An individual’s search behavior often involves a combination of exploratory behavior triggered by sal...
Wouter Weerkamp, Krisztian Balog, Maarten de Rijke