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The tag navigation recommendation with adaptive learning method

  • Wei Jiang*
  • , Xiu Li Pang
  • *Corresponding author for this work
  • School of Management, Harbin Institute of Technology
  • Hei Long Jiang University

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

Abstract

Social Tags are widely used in web 2.0, and they bring the new chance and challenge to the recommender system, which is used to help users deal with information overload and provide personalized services. There are three respects of work done in this paper: firstly, the n-gram based Tag Navigation is presented to provide the assistant support for tag retrieval; secondly, the Average Mutual Information based tag similarity measure is detailed, furthermore this kind of semantic relation is applied to the retrieval intention expansion; thirdly, an approach of ranking based recommendation is presented, and the adaptive learning mechanism is explored. The experiments verify above methods, and result shows the complex features adopted in the recommendation bring improvement by 13.39%.

Original languageEnglish
Title of host publication2012 International Conference on Management Science and Engineering, ICMSE 2012 - 19th Annual Conference Proceedings
Pages46-52
Number of pages7
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 19th Annual International Conference on Management Science and Engineering, ICMSE 2012 - Dallas, TX, United States
Duration: 20 Sep 201222 Sep 2012

Publication series

NameInternational Conference on Management Science and Engineering - Annual Conference Proceedings
ISSN (Print)2155-1847

Conference

Conference2012 19th Annual International Conference on Management Science and Engineering, ICMSE 2012
Country/TerritoryUnited States
CityDallas, TX
Period20/09/1222/09/12

Keywords

  • Average Mutual Information
  • Tag Navigation
  • adaptive learning algorithm
  • personal recommendation
  • retrieval intention expansion

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