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Utilizing re-finding for personalized information retrieval

Authors:

Sarah K. Tyler,

Jian Wang,

Yi ZhangAuthors Info & Claims

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

Pages 1469 - 1472

https://doi.org/10.1145/1871437.1871649

Published: 26 October 2010 Publication History

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Abstract

Individuals often use search engines to return to web pages they have previously visited. This behaviour, called re-finding, accounts for about 38% of all queries. While researchers have shown how re-finding differs from traditionally studied new-findings, research on how to predict and utilize re-finding is limited. In this paper we explore re-finding for personalized search. We compared three machine learning algorithms (decision trees, Bayesian multinomial regression and support vector machines) to identify re-findings. We then propose several re-ranking methods to utilize the prediction, including promoting predicted re-finding URLs and combining re-finding prediction with relevance estimation. The experimental results demonstrate that using re-finding predictions can improve retrieval performance for personalized search.

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Cited By

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Zhou YDou ZWen J(2023)Enhancing Potential Re-Finding in Personalized Search With Hierarchical Memory NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2021.312606635:4(3846-3857)Online publication date: 1-Apr-2023
https://doi.org/10.1109/TKDE.2021.3126066
Guo QChen WWan H(2021)AOL4PS: A Large-scale Data Set for Personalized SearchData Intelligence10.1162/dint_a_001043:4(548-567)Online publication date: 25-Oct-2021
https://doi.org/10.1162/dint_a_00104
Ma ZDou ZBian GWen Jd'Aquin MDietze SHauff CCurry ECudre Mauroux P(2020)PSTIE: Time Information Enhanced Personalized SearchProceedings of the 29th ACM International Conference on Information & Knowledge Management10.1145/3340531.3411877(1075-1084)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3340531.3411877
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Index Terms

Utilizing re-finding for personalized information retrieval
1. Information systems
  1. Information retrieval

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Information & Contributors

Information

Published In

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

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2010

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CIKM '10

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CIKM '10: International Conference on Information and Knowledge Management

October 26 - 30, 2010

ON, Toronto, Canada

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

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Zhou YDou ZWen J(2023)Enhancing Potential Re-Finding in Personalized Search With Hierarchical Memory NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2021.312606635:4(3846-3857)Online publication date: 1-Apr-2023
https://doi.org/10.1109/TKDE.2021.3126066
Guo QChen WWan H(2021)AOL4PS: A Large-scale Data Set for Personalized SearchData Intelligence10.1162/dint_a_001043:4(548-567)Online publication date: 25-Oct-2021
https://doi.org/10.1162/dint_a_00104
Ma ZDou ZBian GWen Jd'Aquin MDietze SHauff CCurry ECudre Mauroux P(2020)PSTIE: Time Information Enhanced Personalized SearchProceedings of the 29th ACM International Conference on Information & Knowledge Management10.1145/3340531.3411877(1075-1084)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3340531.3411877
Zhou YDou ZWen JCaverlee JHu XLalmas MWang W(2020)Enhancing Re-finding Behavior with External Memories for Personalized SearchProceedings of the 13th International Conference on Web Search and Data Mining10.1145/3336191.3371794(789-797)Online publication date: 20-Jan-2020
https://dl.acm.org/doi/10.1145/3336191.3371794
Wu DDong JTang YCapra R(2020)Understanding task preparation and resumption behaviors in cross‐device searchJournal of the Association for Information Science and Technology10.1002/asi.2430771:8(887-901)Online publication date: 7-Jul-2020
https://dl.acm.org/doi/10.1002/asi.24307
Wu DLiang S(2018)Mobile Search Behavious: An In-depth Analysis based on Contexts, APPs, and DevicesSynthesis Lectures on Information Concepts, Retrieval, and Services10.2200/S00831ED1V01Y201802ICR06310:2(i-159)Online publication date: 19-Mar-2018
https://doi.org/10.2200/S00831ED1V01Y201802ICR063
Wu DDong JTang Y(2018)Modeling and Analyzing Information Preparation Behaviors in Cross-Device SearchCross-Cultural Design. Methods, Tools, and Users10.1007/978-3-319-92141-9_18(232-249)Online publication date: 2-Jun-2018
https://doi.org/10.1007/978-3-319-92141-9_18
Sadeghi SBlanco RMika PSanderson MScholer FVallet D(2017)Re-Finding Behaviour in Vertical DomainsACM Transactions on Information Systems10.1145/297559035:3(1-30)Online publication date: 5-Jun-2017
https://dl.acm.org/doi/10.1145/2975590
Balakrishnan VAhmadi KRavana S(2016)Improving retrieval relevance using users’ explicit feedbackAslib Journal of Information Management10.1108/AJIM-07-2015-010668:1(76-98)Online publication date: 18-Jan-2016
https://doi.org/10.1108/AJIM-07-2015-0106
Takeda YOhshima HTanaka KAnderst-Kotsis GIndrawan-Santiago M(2015)Web page revisiting by coordinate page discoveryProceedings of the 17th International Conference on Information Integration and Web-based Applications & Services10.1145/2837185.2837200(1-10)Online publication date: 11-Dec-2015
https://dl.acm.org/doi/10.1145/2837185.2837200
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