poster

Query recovery of short user queries: on query expansion with stopwords

Authors:

SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval

Pages 733 - 734

https://doi.org/10.1145/1835449.1835589

Published: 19 July 2010 Publication History

Get Access

Abstract

User queries to search engines are observed to predominantly contain inflected content words but lack stopwords and capitalization. Thus, they often resemble natural language queries after case folding and stopword removal. Query recovery aims to generate a linguistically well-formed query from a given user query as input to provide natural language processing tasks and cross-language information retrieval (CLIR). The evaluation of query translation shows that translation scores (NIST and BLEU) decrease after case folding, stopword removal, and stemming. A baseline method for query recovery reconstructs capitalization and stopwords, which considerably increases translation scores and significantly increases mean average precision for a standard CLIR task.

References

[1]

E. Brown and A. Coden. Capitalization recovery for text. In Information Retrieval Techniques for Speech Applications, volume 2273 of LNCS, pages 11--22. Springer, 2002.

Digital Library

Google Scholar

[2]

A. Gravano, M. Jansche, and M. Bacchiani. Restoring punctuation and capitalization in transcribed speech. In ICASSP 2009, pages 4741--4744. IEEE, 2009.

Digital Library

Google Scholar

[3]

G. M. D. Nunzio, N. Ferro, T. Mandl, and C. Peters. CLEF 2006: Ad hoc track overview. In Evaluation of Multilingual and Multi-modal Information Retrieval, CLEF 2006, volume 4730 of LNCS. Springer, 2007.

Digital Library

Google Scholar

[4]

S. Ozmutlu, H. Ozmutlu, and A. Spink. Are people asking questions of general web search engines? Online Information Review, 27(6):396--406, 2003.

Crossref

Google Scholar

[5]

A. Spink, D. Wolfram, M. Jansen, and T. Saracevic. Searching the web: The public and their queries. JASIST, 52(3), 2001.

Digital Library

Google Scholar

[6]

J. Teevan, E. Adar, R. Jones, and M. Potts. History repeats itself: Repeat queries in Yahoo's query logs. In SIGIR 2006, pages 703--704. ACM, 2006.

Digital Library

Google Scholar

[7]

J. Xu and W. Croft. Query expansion using local and global document analysis. In SIGIR '96, pages 4--11. ACM, 1996.

Digital Library

Google Scholar

Cited By

View all

Ma ZDou ZXu WZhang XJiang HCao ZWen JDemartini GZuccon GCulpepper JHuang ZTong H(2021)Pre-training for Ad-hoc RetrievalProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482286(1212-1221)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482286

Index Terms

Query recovery of short user queries: on query expansion with stopwords
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing

Recommendations

Disjunctive Sets of Phrase Queries for Diverse Query Suggestion
WI '19: IEEE/WIC/ACM International Conference on Web Intelligence

This paper proposes a method of suggesting expanded queries that disambiguate the original Web query which has multiple interpretations. In order to produce a diverse set of queries including those corresponding to infrequent query intents, our method ...
Cross-lingual query suggestion using query logs of different languages
SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

Query suggestion aims to suggest relevant queries for a given query, which help users better specify their information needs. Previously, the suggested terms are mostly in the same language of the input query. In this paper, we extend it to cross-...
Exploiting query logs for cross-lingual query suggestions

Query suggestion aims to suggest relevant queries for a given query, which helps users better specify their information needs. Previous work on query suggestion has been limited to the same language. In this article, we extend it to cross-lingual query ...

Comments

Information & Contributors

Information

Published In

SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval

July 2010

944 pages

ISBN:9781450301534

DOI:10.1145/1835449

General Chairs:
Fabio Crestani
University of Lugano, CH
,
Stéphane Marchand-Maillet
University of Geneva, CH
,
Program Chairs:
Hsin-Hsi Chen
National Taiwan University, TW
,
Efthimis N. Efthimiadis
University of Washington, USA
,
Jacques Savoy
University of Neuchatel, CH

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2010

Check for updates

Author Tags

Qualifiers

Poster

Conference

SIGIR '10

Sponsor:

SIGIR

SIGIR '10: The 33rd International ACM SIGIR conference on research and development in Information Retrieval

July 19 - 23, 2010

Geneva, Switzerland

Acceptance Rates

SIGIR '10 Paper Acceptance Rate 87 of 520 submissions, 17%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
316
Total Downloads

Downloads (Last 12 months)2
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Ma ZDou ZXu WZhang XJiang HCao ZWen JDemartini GZuccon GCulpepper JHuang ZTong H(2021)Pre-training for Ad-hoc RetrievalProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482286(1212-1221)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482286

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Disjunctive Sets of Phrase Queries for Diverse Query Suggestion

Cross-lingual query suggestion using query logs of different languages

Exploiting query logs for cross-lingual query suggestions