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» A Knowledge Recommend System Based on User Model
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EPIA
2009
Springer
13 years 11 months ago
Item-Based and User-Based Incremental Collaborative Filtering for Web Recommendations
Abstract. In this paper we propose an incremental item-based collaborative filtering algorithm. It works with binary ratings (sometimes also called implicit ratings), as it is typi...
Catarina Miranda, Alípio Mário Jorge
SIGIR
2009
ACM
14 years 2 months ago
On social networks and collaborative recommendation
Social network systems, like last.fm, play a significant role in Web 2.0, containing large amounts of multimedia-enriched data that are enhanced both by explicit user-provided an...
Ioannis Konstas, Vassilios Stathopoulos, Joemon M....
ICTAI
2010
IEEE
13 years 5 months ago
Comparing Approaches to Preference Dominance for Conversational Recommenders
A conversational recommender system iteratively shows a small set of options for its user to choose between. In order to select these options, the system may analyze the queries tr...
Walid Trabelsi, Nic Wilson, Derek G. Bridge, Franc...
TKDE
2012
236views Formal Methods» more  TKDE 2012»
11 years 10 months ago
Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques
— Recommender systems are becoming increasingly important to individual users and businesses for providing personalized recommendations. However, while the majority of algorithms...
Gediminas Adomavicius, YoungOk Kwon
CIKM
2009
Springer
14 years 2 months ago
Collaborative filtering using random neighbours in peer-to-peer networks
Traditionally, collaborative filtering (CF) algorithms used for recommendation operate on complete knowledge. This makes these algorithms hard to employ in a decentralized contex...
Arno Bakker, Elth Ogston, Maarten van Steen