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KDD
2005
ACM
218views Data Mining» more  KDD 2005»
14 years 4 months ago
A maximum entropy web recommendation system: combining collaborative and content features
Web users display their preferences implicitly by navigating through a sequence of pages or by providing numeric ratings to some items. Web usage mining techniques are used to ext...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
ITCC
2005
IEEE
13 years 10 months ago
A Web Recommendation System Based on Maximum Entropy
We propose a Web recommendation system based on a maximum entropy model. Under the maximum entropy principle, we can combine multiple levels of knowledge about users’ navigation...
Xin Jin, Bamshad Mobasher, Yanzan Zhou
AAAI
2006
13 years 5 months ago
Mixed Collaborative and Content-Based Filtering with User-Contributed Semantic Features
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...
Matthew Garden, Gregory Dudek
RECSYS
2010
ACM
13 years 4 months ago
Recommending twitter users to follow using content and collaborative filtering approaches
Recently the world of the web has become more social and more real-time. Facebook and Twitter are perhaps the exemplars of a new generation of social, real-time web services and w...
John Hannon, Mike Bennett, Barry Smyth
WISE
2009
Springer
14 years 1 months ago
A Web Recommender System for Recommending, Predicting and Personalizing Music Playlists
In this paper, we present a Web recommender system for recommending, predicting and personalizing music playlists based on a user model. We have developed a hybrid similarity match...
Zeina Chedrawy, Syed Sibte Raza Abidi