Personalized Item Recommendation using Image-based Filtering
نویسندگان
چکیده
منابع مشابه
Incorporating 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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Recommender systems utilize information retrieval and machine learning techniques for filtering information and can predict whether a user would like an unseen item. User similarity measurement plays an important role in collaborative filtering based recommender systems. In order to improve accuracy of traditional user based collaborative filtering techniques under new user cold-start problem a...
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Article history: Received 23 February 2010 Received in revised form 7 February 2011 Accepted 7 February 2011 Available online 15 February 2011 Communicated by J. Chomicki
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Personalized item recommendation is useful in narrowing down the list of options provided to a user. In this paper, we address the problem scenario where the user is currently holding a basket of items, and the task is to recommend an item to be added to the basket. Here, we assume that items currently in a basket share some association based on an underlying latent need, e.g., ingredients to p...
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Since, most of the organizations present their services electronically, the number of functionally-equivalent web services is increasing as well as the number of users that employ those web services. Consequently, plenty of information is generated by the users and the web services that lead to the users be in trouble in finding their appropriate web services. Therefore, it is required to provi...
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ژورنال
عنوان ژورنال: The Journal of the Korea Contents Association
سال: 2008
ISSN: 1598-4877
DOI: 10.5392/jkca.2008.8.3.001