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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Trust for Intelligent Recommendation

Trust for Intelligent Recommendation

Bhuiyan, Touhid

Paperback

Series: Springerbriefs in Electrical and Computer Engineering

DatabasesGeneral Computers

ISBN10: 1461468949
ISBN13: 9781461468943
Publisher: Springer Nature
Published: Mar 30 2013
Pages: 119
Weight: 0.44
Height: 0.29 Width: 6.14 Depth: 9.21
Language: English

Recommender systems are one of the recent inventions to deal with the ever-growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbors, generated from a database made up of the preferences of past users. In the absence of these ratings, trust between the users could be used to choose the neighbor for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world friend of a friend recommendations. To extend the boundaries of the neighbor, an effective trust inference technique is required.

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