We explore the relation between classical probabilistic models of information retrieval and
the emerging language modeling approaches. It has long been recognized that the primary …

We introduce and create a framework for deriving probabilistic models of Information
Retrieval. The models are nonparametric models of IR obtained in the language model …

For thousands of years people have realized the importance of archiving and finding
information. With the advent of computers, it became possible to store large amounts of …

Because of the world wide web, information retrieval systems are now used by millions of
untrained users all over the world. The search engines that perform the information retrieval …

The University of Massachusetts took on the TREC10 cross-language track with no prior
experience with Arabic, and no Arabic speakers among any of our researchers or students …

This paper follows a formal approach to information retrieval based on statistical language
models. By introducing some simple reformulations of the basic language modeling …

Spoken document retrieval for a specific context is a very trending and interesting area of
research. It makes it convenient for users to search through archives of speech data, which …

Many Information Retrieval (IR) and Natural language processing (NLP) systems require
textual similarity measurement in order to function, and do so with the help of similarity …

In the language modeling approach to information retrieval, Dirichlet prior smoothing
frequently outperforms Jelinek-Mercer smoothing. Both Dirichlet prior and Jelinek-Mercer …

The University of Massachusetts participated in the cross-language and novelty tracks this
year. The cross-language submission was characterized by combination of evidence to …