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» Explaining collaborative filtering recommendations
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AH
2008
Springer
14 years 2 months ago
Locally Adaptive Neighborhood Selection for Collaborative Filtering Recommendations
Abstract. User-to-user similarity is a fundamental component of Collaborative Filtering (CF) recommender systems. In user-to-user similarity the ratings assigned by two users to a ...
Linas Baltrunas, Francesco Ricci
WWW
2004
ACM
14 years 8 months ago
PipeCF: a scalable DHT-based collaborative filtering recommendation system
Collaborative Filtering (CF) technique has proved to be one of the most successful techniques in recommendation systems in recent years. However, traditional centralized CF system...
Bo Xie, Peng Han, Ruimin Shen
WEBI
2009
Springer
14 years 2 months ago
Zero-Sum Reward and Punishment Collaborative Filtering Recommendation Algorithm
In this paper, we propose a novel memory-based collaborative filtering recommendation algorithm. Our algorithm use a new metric named influence weight, which is adjusted with ze...
Nan Li, Chunping Li
ICDM
2008
IEEE
117views Data Mining» more  ICDM 2008»
14 years 2 months ago
Improving Collaborative Filtering Recommendations Using External Data
This paper describes an approach for incorporating externally specified aggregate ratings information into certain types of collaborative filtering (CF) methods. For a statistic...
Akhmed Umyarov, Alexander Tuzhilin
CHI
2006
ACM
14 years 8 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...