Revisit tag-based profiles in the folksonomy: How many tags are sufficient for profiling?

Haoran XIE, An LIU, Fu Lee WANG, Tak Lam WONG, Xiao LIU, Yanghui RAO

Research output: Chapter in Book/Report/Conference proceedingChapters

Abstract

With the prosperity and popularity of social tagging communities, developing an enormous amount of user-generated data with modalities has emerged in recent years. Personalized search based on tag-based profiles, an indispensable and prominent way to assist users to access and retrieve their interested resources, has been extensively studied by research communities. In this paper, we revisit the extant profiling approaches to personalized search in collaborative tagging systems. Specifically, we attempt to answer the following research questions: (i) how many tags are sufficient for user and resource profiling? and (ii) under what circumstances should profile enriching/refining techniques be used to promote the effectiveness of personalized search? The result of our experimental studies in a real-world dataset indicate that the rational size of tags for constructing user/resource profiles does exist. This size can also provide us with an insight into when profiles should be enriched or refined for active/inactive users and resources. We believe the findings of this paper can be quite useful for the future applications in social tagging systems such as user interest predictions or resource recommendations. Copyright © 2017 IEEE.
Original languageEnglish
Title of host publicationProceedings of 2017 IEEE International Conference on Big Data and Smart Computing (BigComp)
Place of PublicationSouth Korea
PublisherIEEE
Pages274-277
ISBN (Print)9781509030156, 9781509030149
Publication statusPublished - 2017

Citation

Xie, H., Liu, A., Wang, F. L., Wong, T.-L., Liu, X., & Rao, Y. (2017). Revisit tag-based profiles in the folksonomy: How many tags are sufficient for profiling?. In Proceedings of 2017 IEEE International Conference on Big Data and Smart Computing (BigComp) (pp. 274-277). South Korea: IEEE.

Keywords

  • Tagging
  • Entropy
  • Frequency control
  • Measurement
  • Frequency conversion
  • Testing
  • Education

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