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Scalable tag recommendation for software information sites

  • Pingyi Zhou
  • , Jin Liu
  • , Zijiang Yang
  • , Guangyou Zhou
  • Wuhan University
  • Central China Normal University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

62 Scopus citations

Abstract

Software developers can search, share and learn development experience, solutions, bug fixes and open source projects in software information sites such as StackOverflow and Freecode. Many software information sites rely on tags to classify their contents, i.e. software objects, in order to improve the performance and accuracy of various operations on the sites. The quality of tags thus has a significant impact on the usefulness of these sites. High quality tags are expected to be concise and can describe the most important features of the software objects.

Original languageEnglish
Title of host publicationSANER 2017 - 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering
EditorsGabriele Bavota, Martin Pinzger, Andrian Marcus
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages272-282
Number of pages11
ISBN (Electronic)9781509055012
DOIs
StatePublished - 21 Mar 2017
Event24th IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2017 - Klagenfurt, Austria
Duration: 21 Feb 201724 Feb 2017

Publication series

NameSANER 2017 - 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering

Conference

Conference24th IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2017
Country/TerritoryAustria
CityKlagenfurt
Period21/02/1724/02/17

Keywords

  • Multi-Classification
  • Software Information Site
  • Software Object
  • Tag Recommendation

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