Recommendation system in social networks with topical attention and probabilistic matrix factorization
نویسندگان
چکیده
منابع مشابه
Towards Social Recommendation based on Probabilistic Matrix Factorization
As an important tool to help users filter Internet information, recommender system has played a very important role wherever in academia or in industrial area. During the past years, different recommendation approaches based on the social network have been proposed with the rapid development of online social networks. Different from the traditional ones which assume all the users are independen...
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Article history: Received 3 September 2012 Received in revised form 27 March 2013 Accepted 4 April 2013 Available online xxxx
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Trust has been used to replace or complement ratingbased similarity in recommender systems, to improve the accuracy of rating prediction. However, people trusting each other may not always share similar preferences. In this paper, we try to fill in this gap by decomposing the original single-aspect trust information into four general trust aspects, i.e. benevolence, integrity, competence, and p...
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Social network websites, such as Facebook, YouTube, Lastfm etc, have become a popular platform for users to connect with each other and share content or opinions. They provide rich information for us to study the influence of user’s social circle in their decision process. In this paper, we are interested in examining the effectiveness of social network information to predict the user’s ratings...
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ژورنال
عنوان ژورنال: PLOS ONE
سال: 2019
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0223967