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  • 标题:Study on Techniques to Improve Diversity in Recommender Systems
  • 本地全文:下载
  • 作者:Vaishnavi.S ; Jayanthi.A ; Karthik.S
  • 期刊名称:International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
  • 印刷版ISSN:2278-1323
  • 出版年度:2012
  • 卷号:1
  • 期号:8
  • 页码:198-201
  • 出版社:Shri Pannalal Research Institute of Technolgy
  • 摘要:Recommender systems play a significant rolein E-Marketing. Many companies got increase in theirsale due to establishing their products in the sites likeAmazon.com, Netflix.com, and Movielens.com etc. Thesesites help the customers to find relevant product to theirinterest. They play as a place where customers can findall kinds of items. These systems should give qualitativerecommendations e.g. in book recommendations, itshould not always tell the books of same authors. Twoimportant qualities are accuracy and diversity.Increasing the diversity decreases the accuracy. Tradeoffbetween accuracy and diversity should be minimized.In this paper, we gave a survey about the techniqueswhich aims to increase the diversity with minimalaccuracy loss.
  • 关键词:Recommender Systems; E-Marketing;Accuracy; Diversity; Social Diversity; Long-Tail;products
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