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Article

Automatic identification of user goals in Web search

Authors:

Junghoo ChoAuthors Info & Claims

WWW '05: Proceedings of the 14th international conference on World Wide Web

Pages 391 - 400

https://doi.org/10.1145/1060745.1060804

Published: 10 May 2005 Publication History

Abstract

There has been recent interests in studying the "goal" behind a user's Web query, so that this goal can be used to improve the quality of a search engine's results. Previous studies have mainly focused on using manual query-log investigation to identify Web query goals. In this paper we study whether and how we can automate this goal-identification process. We first present our results from a human subject study that strongly indicate the feasibility of automatic query-goal identification. We then propose two types of features for the goal-identification task: user-click behavior and anchor-link distribution. Our experimental evaluation shows that by combining these features we can correctly identify the goals for 90% of the queries studied.

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Cited By

Razavian MPaech BTang A(2023)The vision of on-demand architectural knowledge systems as a decision-making companionJournal of Systems and Software10.1016/j.jss.2022.111560198:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.jss.2022.111560
Sguerra BBaranes MHennequin RMoussallam MBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Navigational, Informational or Punk-Rock? An Exploration of Search Intent in the Musical DomainProceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3531308(202-211)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1145/3503252.3531308
Alexander DKusa WP. de Vries AAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)ORCAS-IProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531737(3057-3066)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3531737
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Index Terms

Automatic identification of user goals in Web search
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing
  2. Information systems applications

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Published In

cover image ACM Conferences

WWW '05: Proceedings of the 14th international conference on World Wide Web

May 2005

781 pages

ISBN:1595930469

DOI:10.1145/1060745

Conference Chairs:
Allan Ellis
Southern Cross University
,
Tatsuya Hagino
Keio University

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 10 May 2005

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Razavian MPaech BTang A(2023)The vision of on-demand architectural knowledge systems as a decision-making companionJournal of Systems and Software10.1016/j.jss.2022.111560198:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.jss.2022.111560
Sguerra BBaranes MHennequin RMoussallam MBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Navigational, Informational or Punk-Rock? An Exploration of Search Intent in the Musical DomainProceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3531308(202-211)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1145/3503252.3531308
Alexander DKusa WP. de Vries AAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)ORCAS-IProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531737(3057-3066)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3531737
Shams SSadia BAslam M(2022)Intent Detection in Urdu Queries using Fine-tuned BERT models2022 16th International Conference on Open Source Systems and Technologies (ICOSST)10.1109/ICOSST57195.2022.10016834(1-6)Online publication date: 14-Dec-2022
https://doi.org/10.1109/ICOSST57195.2022.10016834
Natarajan VShanmuganathan S(2022)Understanding Query Intention in Search Queries of Learners in Blended Learning Environments2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA)10.1109/ICCCMLA56841.2022.9989024(308-315)Online publication date: 8-Oct-2022
https://doi.org/10.1109/ICCCMLA56841.2022.9989024
El Zein D(2022)Cognitive Information RetrievalAdvances in Information Retrieval10.1007/978-3-030-99739-7_58(473-479)Online publication date: 5-Apr-2022
https://doi.org/10.1007/978-3-030-99739-7_58
Jiang JLee CYang LSarrafzadeh BHecht BTeevan J(2021)Learning to Represent Human Motives for Goal-directed Web BrowsingProceedings of the 15th ACM Conference on Recommender Systems10.1145/3460231.3474260(361-371)Online publication date: 13-Sep-2021
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Nandi PDas D(2021)Evaluation of Intent Classification Models on Frequently Asked Railway QueriesProceedings of International Conference on Data Science and Applications10.1007/978-981-16-5348-3_3(41-56)Online publication date: 23-Nov-2021
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Ceci MLanotte P(2020)Closed sequential pattern mining for sitemap generationWorld Wide Web10.1007/s11280-020-00839-224:1(175-203)Online publication date: 27-Sep-2020
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Sumikawa YIkejiri R(2020)Feature selection for classifying multi-labeled past eventsInternational Journal on Digital Libraries10.1007/s00799-020-00293-5Online publication date: 8-Sep-2020
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