research-article

Learning to recognize valuable tags

Authors:

John RiedlAuthors Info & Claims

IUI '09: Proceedings of the 14th international conference on Intelligent user interfaces

Pages 87 - 96

https://doi.org/10.1145/1502650.1502666

Published: 08 February 2009 Publication History

Abstract

Many websites use tags as a mechanism for improving item metadata through collective user effort. Users of tagging systems often apply far more tags to an item than a system can display. These tags can range in quality from tags that capture a key facet of an item, to those that are subjective, irrelevant, or misleading. In this paper we explore tag selection algorithms that choose the tags that sites display. Based on 225,000 ratings and survey responses, we conduct offline analyses of 21 tag selection algorithms. We select the three best performing algorithms from our offline analysis, and deploy them live on the MovieLens website to 5,695 users for three months. Based on our results, we offer tagging system designers advice about tag selection algorithms.

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Cited By

Deshpande AEmmanuel M(2022)Context Dependency with User Action in Recommendation SystemSmart Intelligent Computing and Applications, Volume 110.1007/978-981-16-9669-5_43(471-479)Online publication date: 19-Apr-2022
https://doi.org/10.1007/978-981-16-9669-5_43
Yao YHarper FPera SEkstrand MAmatriain XO'Donovan J(2018)Judging similarityProceedings of the 12th ACM Conference on Recommender Systems10.1145/3240323.3240351(288-296)Online publication date: 27-Sep-2018
https://dl.acm.org/doi/10.1145/3240323.3240351
Aggarwal CAggarwal C(2016)Social and Trust-Centric Recommender SystemsRecommender Systems10.1007/978-3-319-29659-3_11(345-384)Online publication date: 29-Mar-2016
https://doi.org/10.1007/978-3-319-29659-3_11
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Index Terms

Learning to recognize valuable tags
1. Human-centered computing
  1. Collaborative and social computing
  2. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

IUI '09: Proceedings of the 14th international conference on Intelligent user interfaces

February 2009

522 pages

ISBN:9781605581682

DOI:10.1145/1502650

General Chairs:
Cristina Conati
University of British Columbia, Canada
,
Mathias Bauer
mineway GmbH, Germany
,
Program Chairs:
Nuria Oliver
Telefonica Research, Spain
,
Dan Weld
University of Washington, USA

Copyright © 2009 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: 08 February 2009

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IUI09: 14th International Conference on Intelligent User Interfaces

February 8 - 11, 2009

Florida, Sanibel Island, USA

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

Deshpande AEmmanuel M(2022)Context Dependency with User Action in Recommendation SystemSmart Intelligent Computing and Applications, Volume 110.1007/978-981-16-9669-5_43(471-479)Online publication date: 19-Apr-2022
https://doi.org/10.1007/978-981-16-9669-5_43
Yao YHarper FPera SEkstrand MAmatriain XO'Donovan J(2018)Judging similarityProceedings of the 12th ACM Conference on Recommender Systems10.1145/3240323.3240351(288-296)Online publication date: 27-Sep-2018
https://dl.acm.org/doi/10.1145/3240323.3240351
Aggarwal CAggarwal C(2016)Social and Trust-Centric Recommender SystemsRecommender Systems10.1007/978-3-319-29659-3_11(345-384)Online publication date: 29-Mar-2016
https://doi.org/10.1007/978-3-319-29659-3_11
Harper FKonstan J(2015)The MovieLens DatasetsACM Transactions on Interactive Intelligent Systems10.1145/28278725:4(1-19)Online publication date: 22-Dec-2015
https://dl.acm.org/doi/10.1145/2827872
Gedikli FJannach D(2013)Improving recommendation accuracy based on item-specific tag preferencesACM Transactions on Intelligent Systems and Technology10.1145/2414425.24144364:1(1-19)Online publication date: 1-Feb-2013
https://dl.acm.org/doi/10.1145/2414425.2414436
Nguyen TRiedl J(2013)Predicting Users’ Preference from Tag RelevanceUser Modeling, Adaptation, and Personalization10.1007/978-3-642-38844-6_23(274-280)Online publication date: 2013
https://doi.org/10.1007/978-3-642-38844-6_23
Liu JWang WChen ZDu XQi Q(2012)A novel user-based collaborative filtering method by inferring tag ratingsACM SIGAPP Applied Computing Review10.1145/2432546.243255012:4(48-57)Online publication date: 1-Dec-2012
https://dl.acm.org/doi/10.1145/2432546.2432550
Wang WChen ZLiu JQi QZhao ZLong BChang YLi H(2012)User-based collaborative filtering on cross domain by tag transfer learningProceedings of the 1st International Workshop on Cross Domain Knowledge Discovery in Web and Social Network Mining10.1145/2351333.2351335(10-17)Online publication date: 12-Aug-2012
https://dl.acm.org/doi/10.1145/2351333.2351335
Qi QChen ZLiu JHui CWu QOssowski SLecca P(2012)Using inferred tag ratings to improve user-based collaborative filteringProceedings of the 27th Annual ACM Symposium on Applied Computing10.1145/2245276.2232110(2008-2013)Online publication date: 26-Mar-2012
https://dl.acm.org/doi/10.1145/2245276.2232110
Kashoob SCaverlee J(2012)Temporal dynamics of communities in social bookmarking systemsSocial Network Analysis and Mining10.1007/s13278-012-0054-z2:4(387-404)Online publication date: 1-Mar-2012
https://doi.org/10.1007/s13278-012-0054-z
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