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Personalized query expansion for the web

Published: 23 July 2007 Publication History

Abstract

The inherent ambiguity of short keyword queries demands for enhanced methods for Web retrieval. In this paper we propose to improve such Web queries by expanding them with terms collected from each user's Personal Information Repository, thus implicitly personalizing the search output. We introduce five broad techniques for generating the additional query keywords by analyzing user data at increasing granularity levels, ranging from term and compound level analysis up to global co-occurrence statistics, as well as to using external thesauri. Our extensive empirical analysis under four different scenarios shows some of these approaches to perform very well, especially on ambiguous queries, producing a very strong increase in the quality of the output rankings. Subsequently, we move this personalized search framework one step further and propose to make the expansion process adaptive to various features of each query. A separate set of experiments indicates the adaptive algorithms to bring an additional statistically significant improvement over the best static expansion approach.

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cover image ACM Conferences
SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
July 2007
946 pages
ISBN:9781595935977
DOI:10.1145/1277741
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: 23 July 2007

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Author Tags

  1. desktop profile
  2. keyword co-occurrences
  3. keyword extraction
  4. personalized web search
  5. query expansion

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SIGIR07
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SIGIR07: The 30th Annual International SIGIR Conference
July 23 - 27, 2007
Amsterdam, The Netherlands

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

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  • (2023)Personalized Query Expansion with Contextual Word EmbeddingsACM Transactions on Information Systems10.1145/362498842:2(1-35)Online publication date: 20-Sep-2023
  • (2023)Serendipitous Book Explorer Using Personalized Associative DictionariesHCI International 2023 – Late Breaking Papers10.1007/978-3-031-48044-7_10(131-150)Online publication date: 21-Nov-2023
  • (2022)Personalized Query Suggestion with Searching Dynamic Flow for Online RecruitmentProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557416(2773-2783)Online publication date: 17-Oct-2022
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  • (2021)You Get What You Chat: Using Conversations to Personalize Search-Based RecommendationsAdvances in Information Retrieval10.1007/978-3-030-72113-8_14(207-223)Online publication date: 27-Mar-2021
  • (2020)Personalized Query SuggestionsProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401331(1645-1648)Online publication date: 25-Jul-2020
  • (2020)Personalized Entity Search by Sparse and Scrutable User ProfilesProceedings of the 2020 Conference on Human Information Interaction and Retrieval10.1145/3343413.3378011(427-431)Online publication date: 14-Mar-2020
  • (2020)Improving News Personalization Through Search LogsBias and Social Aspects in Search and Recommendation10.1007/978-3-030-52485-2_14(152-166)Online publication date: 12-Jul-2020
  • (2020)Using Image Captions and Multitask Learning for Recommending Query ReformulationsAdvances in Information Retrieval10.1007/978-3-030-45439-5_45(681-696)Online publication date: 8-Apr-2020
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