Statistical language models have recently been successfully applied to many information
retrieval problems. A great deal of recent work has shown that statistical language models …

Introduction to Information Retrieval is the first textbook with a coherent treatment of classical
and web information retrieval, including web search and the related areas of text …

In this paper we propose a probabilistic model for online document clus-tering. We use non-
parametric Dirichlet process prior to model the grow-ing number of clusters, and use a prior …

A modern information retrieval system must have the capability to find, organize and present
very different manifestations of information–such as text, pictures, videos or database …

Interpretations of TF-IDF are based on binary independence retrieval, Poisson, information
theory, and language modelling. This paper contributes a review of existing interpretations …

Image segmentation algorithms partition the set of pixels of an image into a specific number
of different, spatially homogeneous groups. We propose a nonparametric Bayesian model …

Most previous work on the recently developed language-modeling approach to information
retrieval focuses on document-specific characteristics, and therefore does not take into …

Until recently there are no common, convenient, and repeatable evaluation methods that
could be easily applied to support fast turn-around development of automatic text …

Collaborative filtering is concerned with making recommendations about items to users.
Most formulations of the problem are specifically designed for predicting user ratings …

We propose a topic based approach to language modelling for ad-hoc information retrieval
(IR). Many smoothed estimators used for the multinomial query model in IR rely upon the …