A group recommender for movies based on content similarity and popularity
作者: Maria S. PeraYiu-Kai Ng
作者单位: 1Computer Science Department, Brigham Young University, Provo, UT 84602, USA
刊名: Information Processing and Management, 2013, Vol.49 (3), pp.673-687
来源数据库: Elsevier Journal
DOI: 10.1016/j.ipm.2012.07.007
关键词: Group recommenderContent-similarityPopularityMovie
英文摘要: Abstract(#br)People are gregarious by nature, which explains why group activities, from colleagues sharing a meal to friends attending a book club event together, are the social norm. Online group recommenders identify items of interest, such as restaurants, movies, and books, that satisfy the collective needs of a group (rather than the interests of individual group members). With a number of new movies being released every week, online recommenders play a significant role in suggesting movies for family members or groups of friends/people to watch, either at home or at movie theaters. Making group recommendations relevant to the joint interests of a group, however, is not a trivial task due to the diversity in preferences among group members. To address this issue, we introduce GroupReM...
全文获取路径: Elsevier  (合作)
影响因子:0.817 (2012)

  • popularity 名望
  • similarity 相似性
  • content 品位
  • based 基于
  • group