• DocumentCode
    578476
  • Title

    Method of tags recommendation for blogs: A comparative study

  • Author

    Tang, Li-juan ; Zhang, Cheng-zhi

  • Author_Institution
    Dept. of Inf. Manage., Nanjing Univ. of Sci. & Technol., Nanjing, China
  • Volume
    5
  • fYear
    2012
  • fDate
    15-17 July 2012
  • Firstpage
    2037
  • Lastpage
    2040
  • Abstract
    Tags are products of Web 2.0. They play an important role in user modeling, friends or information recommendation. In this paper, keywords from blogs are extracted by using TextRank and TF*IDF algorithms respectively. The keywords are used to tag recommendation. Experiment results show that the performance of these two algorithms is very closely.
  • Keywords
    Internet; Web sites; recommender systems; TextRank; Web 2.0; blogs; information recommendation; tags recommendation; user modeling; Abstracts; Blogs; Electronic mail; Social tagging; TF*IDF; Tags recommendation; TextRank;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
  • Conference_Location
    Xian
  • ISSN
    2160-133X
  • Print_ISBN
    978-1-4673-1484-8
  • Type

    conf

  • DOI
    10.1109/ICMLC.2012.6359689
  • Filename
    6359689
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=578476