NDLI: Document Language Models, Query Models, and Risk Minimization for Information Retrieval

Content Provider	ACM Digital Library
Author	Zhai, Chengxiang Lafferty, John
Abstract	We present a framework for information retrieval that combines document models and query models using a probabilistic ranking function based on Bayesian decision theory. The framework suggests an operational retrieval model that extends recent developments in the language modeling approach to information retrieval. A language model for each document is estimated, as well as a language model for each query, and the retrieval problem is cast in terms of risk minimization. The query language model can be exploited to model user preferences, the context of a query, synonomy and word senses. While recent work has incorporated word translation models for this purpose, we introduce a new method using Markov chains defined on a set of documents to estimate the query models. The Markov chain method has connections to algorithms from link analysis and social networks. The new approach is evaluated on TREC collections and compared to the basic language modeling approach and vector space models together with query expansion using Rocchio. Significant improvements are obtained over standard query expansion methods for strong baseline TF-IDF systems, with the greatest improvements attained for short queries on Web data.
Starting Page	251
Ending Page	259
Page Count	9
File Format	PDF
ISSN	01635840
DOI	10.1145/3130348.3130375
Journal	ACM SIGIR Forum (SIGF)
Volume Number	51
Issue Number	2
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1978-08-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Content Type	Text
Resource Type	Article
Subject	Management Information Systems Hardware and Architecture

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Document Language Models, Query Models, and Risk Minimization for Information Retrieval (2001)

Document language models, query models, and risk minimization for information retrieval (2001)

Document Language Models, Query Models, and Risk Minimization for Information Retrieval (2001)

Risk minimization and language modeling in text retrieval dissertation abstract

Document representation models for retrieval systems

Document language models, query models, and risk minimization for information retrieval

Outline of a dynamic self-tuning and adaptive information retrieval system

Phrasal translation and query expansion techniques for cross-language information retrieval

QQL: A DB&IR Query Language

Document Language Models, Query Models, and Risk Minimization for Information Retrieval

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