research-article

Clickthrough-based translation models for web search: from word models to phrase models

Authors:

Jian-Yun NieAuthors Info & Claims

CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

Pages 1139 - 1148

https://doi.org/10.1145/1871437.1871582

Published: 26 October 2010 Publication History

Abstract

Web search is challenging partly due to the fact that search queries and Web documents use different language styles and vocabularies. This paper provides a quantitative analysis of the language discrepancy issue, and explores the use of clickthrough data to bridge documents and queries. We assume that a query is parallel to the titles of documents clicked on for that query. Two translation models are trained and integrated into retrieval models: A word-based translation model that learns the translation probability between single words, and a phrase-based translation model that learns the translation probability between multi-term phrases. Experiments are carried out on a real world data set. The results show that the retrieval systems that use the translation models outperform significantly the systems that do not. The paper also demonstrates that standard statistical machine translation techniques such as word alignment, bilingual phrase extraction, and phrase-based decoding, can be adapted for building a better Web document retrieval system.

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Roy PSharma CGao CValegerepura KFrommholz IHopfgartner FLee MOakes MLalmas MZhang MSantos R(2023)Deep Query Rewriting For GeocodingProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3615466(4801-4807)Online publication date: 21-Oct-2023
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Clickthrough-based translation models for web search: from word models to phrase models

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cover image ACM Conferences

CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

October 2010

2036 pages

ISBN:9781450300995

DOI:10.1145/1871437

General Chair:
Jimmy Huang
York University, Canada
,
Program Chairs:
Nick Koudas
University of Toronto, Canada
,
Gareth Jones
Dublin City University, Ireland
,
Xindong Wu
University of Vermont, USA
,
Kevyn Collins-Thompson
Microsoft Research, USA
,
Aijun An
York University, Canada

Copyright © 2010 ACM.

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Published: 26 October 2010

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Cited By

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https://doi.org/10.1007/978-3-031-81477-8_4
Roy PSharma CGao CValegerepura KFrommholz IHopfgartner FLee MOakes MLalmas MZhang MSantos R(2023)Deep Query Rewriting For GeocodingProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3615466(4801-4807)Online publication date: 21-Oct-2023
https://dl.acm.org/doi/10.1145/3583780.3615466
Chen HDou ZZhu QZuo XWen J(2023)Integrating Representation and Interaction for Context-Aware Document RankingACM Transactions on Information Systems10.1145/352995541:1(1-23)Online publication date: 10-Jan-2023
https://dl.acm.org/doi/10.1145/3529955
Hambarde KProença H(2023)Information Retrieval: Recent Advances and BeyondIEEE Access10.1109/ACCESS.2023.329577611(76581-76604)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3295776
Yang HGonçalves T(2023)Field features: The impact in learning to rank approachesApplied Soft Computing10.1016/j.asoc.2023.110183138(110183)Online publication date: May-2023
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