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SIGIR
2011
ACM
12 years 7 months ago
Collaborative competitive filtering: learning recommender using context of user choice
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...
AIR
1999
136views more  AIR 1999»
13 years 3 months ago
A Framework for Collaborative, Content-Based and Demographic Filtering
We discuss learning a profile of user interests for recommending information sources such as Web pages or news articles. We describe the types of information available to determin...
Michael J. Pazzani
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
ICDE
2007
IEEE
173views Database» more  ICDE 2007»
13 years 6 months ago
A Hybrid Recommender System for Context-aware Recommendations of Mobile Applications
The goal of the work in this paper is towards the incorporation of context in recommender systems in the domain of mobile applications. The approach recommends mobile applications...
Wolfgang Wörndl, Christian Schüller, Rol...
CHI
2006
ACM
14 years 4 months ago
Accounting for taste: using profile similarity to improve recommender systems
Recommender systems have been developed to address the abundance of choice we face in taste domains (films, music, restaurants) when shopping or going out. However, consumers curr...
Philip Bonhard, Clare Harries, John D. McCarthy, M...