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文章基本信息

  • 标题:Improving Recommendations Assortment using Ranking Functions
  • 本地全文:下载
  • 作者:Karuna Latha Thanukula ; Manda Ashok Kumar ; Betam Suresh
  • 期刊名称:International Journal of Computer Trends and Technology
  • 电子版ISSN:2231-2803
  • 出版年度:2013
  • 卷号:4
  • 期号:8-5
  • 出版社:Seventh Sense Research Group
  • 摘要:Recommendation Systems are becoming more familiar these days to individual users and organizations because of the personalized recommendations. This paper helps to know more about how a recommendation is provided based on the ranking function that can be employed matching to the proposed scenario. With this concept we can also suggest the way to improve the recommendation technique based on the market requirements. The ranking based technique that is involved here to give recommendations will have substantially higher aggregate diversity across all users.
  • 关键词:Recommendation systems; personalized recommendations; ranking function; aggregate diversity
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