Tag-Based Recommendation

Research output: Contribution to book/anthology/report/conference proceedingBook chapterResearchpeer-review

16 Citations (Scopus)

Abstract

Social tagging is an information classification paradigm where the users themselves are given the power to describe and categorize content for their own purposes using tags. The popularity of social tagging, and the ease with which such tags can be generated, assigned, and collected, has sparked significant research interest in tags and their possible applications. One such application is tag-based recommendation: generating better recommendations by incorporating tags into the recommendation process. This chapter provides an overview of the state-of-the-art approaches to tag-based item recommendation, organised by the class of recommendation algorithms that is augmented with tags, such as collaborative filtering, dimensionality reduction, graph-based recommendation, content-based filtering, machine learning, and hybrid recommendation. The chapter also offers an overview of the most important methods for recommending which tags to apply to content. Finally, the chapter discusses the open research problems in tag-based recommendation and what would be needed to address them.
Original languageEnglish
Title of host publicationSocial Information Access
EditorsPeter Brusilovsky, Daqing He
Number of pages39
PublisherSpringer
Publication date1 Jan 2018
Pages441-479
Chapter12
ISBN (Print)978-3-319-90091-9
ISBN (Electronic)978-3-319-90092-6
DOIs
Publication statusPublished - 1 Jan 2018
SeriesLecture Notes in Computer Science
Volume10100
ISSN0302-9743

Keywords

  • social tagging
  • social bookmarking
  • collaborative filtering
  • recommender systems
  • content-based recommendation
  • machine learning
  • hybrid recommendation
  • tag recommendation
  • tag-based recommendation

Fingerprint Dive into the research topics of 'Tag-Based Recommendation'. Together they form a unique fingerprint.

  • Cite this

    Bogers, T. (2018). Tag-Based Recommendation. In P. Brusilovsky, & D. He (Eds.), Social Information Access (pp. 441-479). Springer. Lecture Notes in Computer Science, Vol.. 10100 https://doi.org/10.1007/978-3-319-90092-6_12