research-article

Tag data and personalized information retrieval

Authors:

Mark J. Carman,

Fabio CrestaniAuthors Info & Claims

SSM '08: Proceedings of the 2008 ACM workshop on Search in social media

Pages 27 - 34

https://doi.org/10.1145/1458583.1458591

Published: 30 October 2008 Publication History

Abstract

Researchers investigating personalization techniques for Web Information Retrieval face a challenge; that the data required to perform evaluations, namely query logs and click-through data, is not readily available due to valid privacy concerns. One option for researchers is to perform a user study, however, such experiments are often limited to small (and sometimes biased) samples of users, restricting somewhat the conclusions that can be drawn. Alternatively, researchers can look for publicly available data that can be used to approximate query logs and click-through data. Recently it has been shown that the information contained in social bookmarking (tagging) systems may be useful for improving Web search.

We investigate the use of tag data for evaluating personalized retrieval systems involving thousands of users. Using data from the social bookmarking site del.icio.us, we demonstrate how one can rate the quality of personalized retrieval results. Furthermore, we conduct experiments involving various smoothing techniques and profile settings, which show that a user's "bookmark history" can be used to improve search results via personalization. Analogously to studies involving implicit feedback mechanisms in IR, which have found that profiles based on the content of clicked URLs outperform those based on past queries alone, we find that profiles based on the content of bookmarked URLs are generally superior to those based on tags alone.

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Cited By

Sadat IKechid S(2023)Multiple Emotional Profile Representation for Personalized Information Retrieval Systems2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)10.1109/AICCSA59173.2023.10479251(1-4)Online publication date: 4-Dec-2023
https://doi.org/10.1109/AICCSA59173.2023.10479251
Ashtari NAlamzadeh PGanapathy GChilana P(2022)PONI: A Personalized Onboarding Interface for Getting Inspiration and Learning About AR/VR CreationNordic Human-Computer Interaction Conference10.1145/3546155.3546642(1-14)Online publication date: 8-Oct-2022
https://dl.acm.org/doi/10.1145/3546155.3546642
Chen YLai KLiu DChen M(2022)TAGNet: Triplet-Attention Graph Networks for Hashtag RecommendationIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2021.307459932:3(1148-1159)Online publication date: Mar-2022
https://doi.org/10.1109/TCSVT.2021.3074599
Show More Cited By

Index Terms

Tag data and personalized information retrieval
1. Information systems
  1. Information retrieval

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Published In

cover image ACM Conferences

SSM '08: Proceedings of the 2008 ACM workshop on Search in social media

October 2008

106 pages

ISBN:9781605582580

DOI:10.1145/1458583

Program Chairs:
Ian Soboroff
National Institute of Standards and Technology
,
Eugene Agichtein
Emory University
,
Ravi Kumar
Yahoo! Research

Copyright © 2008 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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Published: 30 October 2008

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October 30, 2008

California, Napa Valley, USA

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CIKM '25

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Cited By

Sadat IKechid S(2023)Multiple Emotional Profile Representation for Personalized Information Retrieval Systems2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)10.1109/AICCSA59173.2023.10479251(1-4)Online publication date: 4-Dec-2023
https://doi.org/10.1109/AICCSA59173.2023.10479251
Ashtari NAlamzadeh PGanapathy GChilana P(2022)PONI: A Personalized Onboarding Interface for Getting Inspiration and Learning About AR/VR CreationNordic Human-Computer Interaction Conference10.1145/3546155.3546642(1-14)Online publication date: 8-Oct-2022
https://dl.acm.org/doi/10.1145/3546155.3546642
Chen YLai KLiu DChen M(2022)TAGNet: Triplet-Attention Graph Networks for Hashtag RecommendationIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2021.307459932:3(1148-1159)Online publication date: Mar-2022
https://doi.org/10.1109/TCSVT.2021.3074599
Balog KRadlinski FKaratzoglou ADiaz FShah CSuel TCastells PJones RSakai T(2021)On Interpretation and Measurement of Soft Attributes for RecommendationProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3462893(890-899)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3404835.3462893
Lobo LBirbal K(2021)A Novel Method for Analyzing Best Pages Generated by Query Term Synonym CombinationProceedings of International Conference on Data Science and Applications10.1007/978-981-16-5120-5_33(441-455)Online publication date: 23-Nov-2021
https://doi.org/10.1007/978-981-16-5120-5_33
Liu JLiu CBelkin N(2020)Personalization in text information retrievalJournal of the Association for Information Science and Technology10.1002/asi.2423471:3(349-369)Online publication date: 28-Jan-2020
https://dl.acm.org/doi/10.1002/asi.24234
Lu WDing HJiang J(2018)A document expansion framework for tag-based image retrievalAslib Journal of Information Management10.1108/AJIM-05-2017-013370:1(47-65)Online publication date: 15-Jan-2018
https://doi.org/10.1108/AJIM-05-2017-0133
Samarawickrama SKarunasekera SHarwood AKotagiri R(2017)Search Result Personalization in Twitter Using Neural Word EmbeddingsBig Data Analytics and Knowledge Discovery10.1007/978-3-319-64283-3_18(244-258)Online publication date: 3-Aug-2017
https://doi.org/10.1007/978-3-319-64283-3_18
Ould Amer NMulhem PGéry M(2017)Personalized Parsimonious Language Models for User Modeling in Social Bookmaking SystemsAdvances in Information Retrieval10.1007/978-3-319-56608-5_52(582-588)Online publication date: 8-Apr-2017
https://doi.org/10.1007/978-3-319-56608-5_52
Pardhi DBorase L(2016)User-perceptive image search using complex multiple word based query (An efficient image search process using complex multiple word based query)2016 10th International Conference on Intelligent Systems and Control (ISCO)10.1109/ISCO.2016.7727115(1-6)Online publication date: Jan-2016
https://doi.org/10.1109/ISCO.2016.7727115
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