Journal article

A survey of collaborative filtering techniques

Su X, Taghi M.Khoshgoftaar ...see all

Advances in Artificial Intelligence, vol. 2009, issue Section 3 (2009) pp. 1-19

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Every day, we are inundated with choices and options. What to wear? What movie to rent? What stock to buy? What blog post to read? The sizes of these decision domains are frequently massive: Netflix has over 17,000 movies in its selection [15], and has over 410,000 titles in its Kindle store alone [7]. Supporting discovery in informa- tion spaces of this magnitude is a significant challenge. Even simple decisions — what movie should I see this weekend? — can be difficult without prior direct knowledge of the candidates. Historically, people have relied on recommendations and mentions from their peers or the advice of experts to support decisions and dis- cover new material. They discuss the week’s blockbuster over the water cooler, they read reviews in the newspaper’s entertainment section, or they ask a librarian to suggest a book. They may trust their local the- ater manager or news stand to narrow down their choices, or turn on the TV and watch whatever happens to be playing.

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  • Xiaoyan Su

  • Taghi M.Khoshgoftaar

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