Incorporating Multiple Attributes in Social Networks to Enhance the Collaborative Filtering Recommendation Algorithm
نویسندگان
چکیده
منابع مشابه
Incorporating Multiple Attributes in Social Networks to Enhance the Collaborative Filtering Recommendation Algorithm
In view of the existing user similarity calculation principle of recommendation algorithm is single, and recommender system accuracy is not well, we propose a novel social multi-attribute collaborative filtering algorithm (SoMu). We first define the user attraction similarity by users’ historical rated behaviors using graph theory, and secondly, define the user interaction similarity by users’ ...
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Predicting people other people may like has recently become an important task in many online social networks. Traditional collaborative filtering approaches are popular in recommender systems to effectively predict user preferences for items. However, in online social networks people have a dual role as both “users” and “items”, e.g., both initiating and receiving contacts. Here the assumption ...
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Commercial enterprises employee data mining techniques to recommend products to their customers. This recommendation is based on similar purchasing histories, as well as similarities between users and similarities between products. It typically involves analyzing a specific domain such as movies or books to make predictions as to which user is likely to want which product, increasing sales and ...
متن کاملAn Improved Recommendation Algorithm in Collaborative Filtering
In Electronic Commerce it is not easy for customers to find the best suitable goods as more and more information is placed on line. In order to provide information of high value a customized recommender system is required. One of the typical information retrieval techniques for recommendation systems in Electronic Commerce is collaborative filtering which is based on the ratings of other custom...
متن کاملIncorporating Personalized Contextual Information in Item-based Collaborative Filtering Recommendation
After reviewing the prior work and problem of collaborative filtering recommendation approaches, an approach incorporating personalized contextual information in item-based collaborative filtering is proposed to solve the problem. The approach provides recommendations based on user personalized contextual information besides the typical information on users and items used in most of the current...
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ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2016
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2016.070408