research-article

Efficient Tag Recommendation for Real-Life Data

Authors:

Evangelos MiliosAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology (TIST), Volume 3, Issue 1

Article No.: 2, Pages 1 - 21

https://doi.org/10.1145/2036264.2036266

Published: 01 October 2011 Publication History

Abstract

Despite all of the advantages of tags as an easy and flexible information management approach, tagging is a cumbersome task. A set of descriptive tags has to be manually entered by users whenever they post a resource. This process can be simplified by the use of tag recommendation systems. Their objective is to suggest potentially useful tags to the user. We present a hybrid tag recommendation system together with a scalable, highly efficient system architecture. The system is able to utilize user feedback to tune its parameters to specific characteristics of the underlying tagging system and adapt the recommendation models to newly added content. The evaluation of the system on six real-life datasets demonstrated the system’s ability to combine tags from various sources (e.g., resource content or tags previously used by the user) to achieve the best quality of recommended tags. It also confirmed the importance of parameter tuning and content adaptation. A series of additional experiments allowed us to better understand the characteristics of the system and tagging datasets and to determine the potential areas for further system development.

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Cited By

Xu YZhao XJiang ZQiu ZHei LLi R(2023)Intelligent Semantic Annotation for Mobile Services for IoT Computing from Heterogeneous DataMobile Networks and Applications10.1007/s11036-023-02091-028:1(348-358)Online publication date: 7-Mar-2023
https://dl.acm.org/doi/10.1007/s11036-023-02091-0
Lin YParra DTrattner CBrusilovsky P(2022)Tag-based information access in image collections: insights from log and eye-gaze analysesKnowledge and Information Systems10.1007/s10115-019-01343-461:3(1715-1742)Online publication date: 11-Mar-2022
https://dl.acm.org/doi/10.1007/s10115-019-01343-4
Najafabadi MNair MMohamed A(2021)Tag recommendation model using feature learning via word embedding2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)10.1109/SAMI50585.2021.9378621(000305-000310)Online publication date: 21-Jan-2021
https://doi.org/10.1109/SAMI50585.2021.9378621
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Index Terms

Efficient Tag Recommendation for Real-Life Data
1. Information systems
  1. World Wide Web
    1. Web applications
    2. Web services

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Published In

cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 3, Issue 1

October 2011

391 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/2036264

Issue’s Table of Contents

Copyright © 2011 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 October 2011

Accepted: 01 January 2011

Revised: 01 January 2011

Received: 01 August 2010

Published in TIST Volume 3, Issue 1

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Cited By

Xu YZhao XJiang ZQiu ZHei LLi R(2023)Intelligent Semantic Annotation for Mobile Services for IoT Computing from Heterogeneous DataMobile Networks and Applications10.1007/s11036-023-02091-028:1(348-358)Online publication date: 7-Mar-2023
https://dl.acm.org/doi/10.1007/s11036-023-02091-0
Lin YParra DTrattner CBrusilovsky P(2022)Tag-based information access in image collections: insights from log and eye-gaze analysesKnowledge and Information Systems10.1007/s10115-019-01343-461:3(1715-1742)Online publication date: 11-Mar-2022
https://dl.acm.org/doi/10.1007/s10115-019-01343-4
Najafabadi MNair MMohamed A(2021)Tag recommendation model using feature learning via word embedding2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)10.1109/SAMI50585.2021.9378621(000305-000310)Online publication date: 21-Jan-2021
https://doi.org/10.1109/SAMI50585.2021.9378621
M. Belém FM. Almeida JA. Gonçalves M(2020)Tagging and Tag RecommendationCyberspace10.5772/intechopen.82242Online publication date: 17-Jun-2020
https://doi.org/10.5772/intechopen.82242
Belém FSilva Rde Andrade CPerson GMingote FBallet RAlponti Hde Oliveira HAlmeida JGonçalves M(2020)“Fixing the curse of the bad product descriptions” – Search-boosted tag recommendation for E-commerce productsInformation Processing & Management10.1016/j.ipm.2020.10228957:5(102289)Online publication date: Sep-2020
https://doi.org/10.1016/j.ipm.2020.102289
Shoja BTabrizi N(2019)Tags-Aware Recommender Systems: A Systematic Review2019 IEEE International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD)10.1109/BCD.2019.8884850(11-18)Online publication date: May-2019
https://doi.org/10.1109/BCD.2019.8884850
Belém FHeringer AAlmeida JGonçalves M(2019)Exploiting syntactic and neighbourhood attributes to address cold start in tag recommendationInformation Processing & Management10.1016/j.ipm.2018.12.00956:3(771-790)Online publication date: May-2019
https://doi.org/10.1016/j.ipm.2018.12.009
Belém FAlmeida JGonçalves M(2017)A survey on tag recommendation methodsJournal of the Association for Information Science and Technology10.1002/asi.2373668:4(830-844)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1002/asi.23736
Belém FBatista CSantos RAlmeida JGonçalves M(2016)Beyond RelevanceACM Transactions on Intelligent Systems and Technology10.1145/28011307:3(1-34)Online publication date: 1-Feb-2016
https://dl.acm.org/doi/10.1145/2801130
Nwana AChen T(2016)QUOTE: “Querying” Users as Oracles in Tag Engines a Semi-Supervised Learning Approach to Personalized Image Tagging2016 IEEE International Symposium on Multimedia (ISM)10.1109/ISM.2016.0016(30-37)Online publication date: Dec-2016
https://doi.org/10.1109/ISM.2016.0016
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