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Optimizing two stage bigram language models for IR

Authors:

Sara Javanmardi,

Jianfeng Gao,

Kuansan WangAuthors Info & Claims

WWW '10: Proceedings of the 19th international conference on World wide web

Pages 1125 - 1126

https://doi.org/10.1145/1772690.1772836

Published: 26 April 2010 Publication History

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Abstract

Although higher order language models (LMs) have shown benefit of capturing word dependencies for Information retrieval(IR), the tuning of the increased number of free parameters remains a formidable engineering challenge. Consequently,in many real world retrieval systems, applying higher order LMs is an exception rather than the rule. In this study, we address the parameter tuning problem using a framework based on a linear ranking model in which different component models are incorporated as features. Using unigram and bigram LMs with 2 stage smoothing as examples, we show that our method leads to a bigram LM that outperforms significantly its unigram counterpart and the well-tuned BM25 model.

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Cited By

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Orimaye SAlhashmi SSiew E(2013)Can predicate-argument structures be used for contextual opinion retrieval from blogs?World Wide Web10.1007/s11280-012-0170-816:5-6(763-791)Online publication date: 1-Nov-2013
https://dl.acm.org/doi/10.1007/s11280-012-0170-8
Li YHsu BZhai CWang KMa WNie JBaeza-Yates RChua TCroft W(2011)Unsupervised query segmentation using clickthrough for information retrievalProceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval10.1145/2009916.2009957(285-294)Online publication date: 24-Jul-2011
https://dl.acm.org/doi/10.1145/2009916.2009957
Orimaye SSadagopan SRamamritham KKumar ARavindra MBertino EKumar R(2011)Sentence-level contextual opinion retrievalProceedings of the 20th international conference companion on World wide web10.1145/1963192.1963351(403-408)Online publication date: 28-Mar-2011
https://dl.acm.org/doi/10.1145/1963192.1963351
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Index Terms

Optimizing two stage bigram language models for IR
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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Published In

WWW '10: Proceedings of the 19th international conference on World wide web

April 2010

1407 pages

ISBN:9781605587998

DOI:10.1145/1772690

General Chairs:
Michael Rappa
North Carolina State University, USA
,
Paul Jones
University of North Carolina at Chapel Hill, USA
,
Program Chairs:
Juliana Freire
University of Utah, USA
,
Soumen Chakrabarti
Indian Institute of Technology, India

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Association for Computing Machinery

New York, NY, United States

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Published: 26 April 2010

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WWW '10

WWW '10: The 19th International World Wide Web Conference

April 26 - 30, 2010

North Carolina, Raleigh, USA

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Orimaye SAlhashmi SSiew E(2013)Can predicate-argument structures be used for contextual opinion retrieval from blogs?World Wide Web10.1007/s11280-012-0170-816:5-6(763-791)Online publication date: 1-Nov-2013
https://dl.acm.org/doi/10.1007/s11280-012-0170-8
Li YHsu BZhai CWang KMa WNie JBaeza-Yates RChua TCroft W(2011)Unsupervised query segmentation using clickthrough for information retrievalProceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval10.1145/2009916.2009957(285-294)Online publication date: 24-Jul-2011
https://dl.acm.org/doi/10.1145/2009916.2009957
Orimaye SSadagopan SRamamritham KKumar ARavindra MBertino EKumar R(2011)Sentence-level contextual opinion retrievalProceedings of the 20th international conference companion on World wide web10.1145/1963192.1963351(403-408)Online publication date: 28-Mar-2011
https://dl.acm.org/doi/10.1145/1963192.1963351
Orimaye SAlhashmi SEu-Gene S(2011)Using predicate-argument structures for context-dependent opinion retrievalProceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part II10.1007/978-3-642-25856-5_29(386-402)Online publication date: 17-Dec-2011
https://dl.acm.org/doi/10.1007/978-3-642-25856-5_29
Orimaye SAlhashmi SEu-Gene S(2011)Semantic-based opinion retrieval using predicate-argument structures and subjective adjectivesProceedings of the 7th Asia conference on Information Retrieval Technology10.1007/978-3-642-25631-8_34(372-385)Online publication date: 18-Dec-2011
https://dl.acm.org/doi/10.1007/978-3-642-25631-8_34

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A novel retrieval approach reflecting variability of syntactic phrase representation

Hindi Word Sense Disambiguation Using Lesk Approach on Bigram and Trigram Words

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