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CISS
2008
IEEE
13 years 11 months ago
A lower-bound on the number of rankings required in recommender systems using collaborativ filtering
— We consider the situation where users rank items from a given set, and each user ranks only a (small) subset of all items. We assume that users can be classified into C classe...
Peter Marbach
WWW
2008
ACM
14 years 5 months ago
Feature weighting in content based recommendation system using social network analysis
We propose a hybridization of collaborative filtering and content based recommendation system. Attributes used for content based recommendations are assigned weights depending on ...
Souvik Debnath, Niloy Ganguly, Pabitra Mitra
RECSYS
2009
ACM
13 years 11 months ago
Harnessing the power of "favorites" lists for recommendation systems
We propose a novel collaborative recommendation approach to take advantage of the information available in user-created lists. Our approach assumes associations among any two item...
Maryam Khezrzadeh, Alex Thomo, William W. Wadge
KAIS
2011
102views more  KAIS 2011»
12 years 12 months ago
Symbolic data analysis tools for recommendation systems
Recommendation Systems have become an important tool to cope with the information overload problem by acquiring data about the user behavior. After tracing the user behavior, throu...
Byron Leite Dantas Bezerra, Francisco de Assis Ten...
ICDM
2008
IEEE
117views Data Mining» more  ICDM 2008»
13 years 11 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