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Effective and efficient user interaction for long queries

Published: 20 July 2008 Publication History

Abstract

Handling long queries can involve either pruning the query to retain only the important terms (reduction), or expanding the query to include related concepts (expansion). While automatic techniques to do so exist, roughly 25% performance improvements in terms of MAP have been realized in past work through interactive variants. We show that selectively reducing or expanding a query leads to an average improvement of 51% in MAP over the baseline for standard TREC test collections. We demonstrate how user interaction can be used to achieve this improvement. Most interaction techniques present users with a fixed number of options for all queries. We achieve improvements by interacting less with the user, i.e., we present techniques to identify the optimal number of options to present to users, resulting in an interface with an average of 70% fewer options to consider. Previous algorithms supporting interactive reduction and expansion are exponential in nature. To extend their utility to operational environments, we present techniques to make the complexity of the algorithms polynomial. We finally present an analysis of long queries that continue to exhibit poor performance in spite of our new techniques.

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    cover image ACM Conferences
    SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
    July 2008
    934 pages
    ISBN:9781605581644
    DOI:10.1145/1390334
    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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    Published: 20 July 2008

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    Author Tags

    1. interactive retrieval efficiency
    2. query analysis
    3. query expansion
    4. query reduction
    5. user interaction

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    • (2021)Query Reformulation for Descriptive Queries of Jargon Words Using a Knowledge Graph based on a DictionaryProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482382(854-862)Online publication date: 26-Oct-2021
    • (2019)Query Reconstruction in Medical Case Description Using Query Performance Predictors2019 10th International Conference on Information Technology in Medicine and Education (ITME)10.1109/ITME.2019.00046(163-168)Online publication date: Aug-2019
    • (2019)Collaborative feature location in models through automatic query expansionAutomated Software Engineering10.1007/s10515-019-00251-926:1(161-202)Online publication date: 1-Mar-2019
    • (2018)Linguistic Patterns and Cross Modality-based Image Retrieval for Complex QueriesProceedings of the 2018 ACM on International Conference on Multimedia Retrieval10.1145/3206025.3206050(257-265)Online publication date: 5-Jun-2018
    • (2018)Online Learning for Long-Query Reduction in Interactive Search for Experienced WorkersHuman Aspects of IT for the Aged Population. Acceptance, Communication and Participation10.1007/978-3-319-92034-4_28(366-376)Online publication date: 1-Jun-2018
    • (2017)Can Short Queries Be Even Shorter?Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3121050.3121056(43-50)Online publication date: 1-Oct-2017
    • (2017)New technique to deal with verbose queries in social book searchProceedings of the International Conference on Web Intelligence10.1145/3106426.3106481(799-806)Online publication date: 23-Aug-2017
    • (2016)Complex-query web image search with concept-based relevance estimationWorld Wide Web10.1007/s11280-015-0357-x19:2(247-264)Online publication date: 1-Mar-2016
    • (2016)Assessment of learning to rank methods for query expansionJournal of the Association for Information Science and Technology10.1002/asi.2347667:6(1345-1357)Online publication date: 1-Jun-2016
    • (2015)Information Retrieval with Verbose QueriesProceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/2766462.2767877(1121-1124)Online publication date: 9-Aug-2015
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