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» Methods for boosting recommender systems
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AIA
2007
13 years 9 months ago
Adaptive preference elicitation for top-K recommendation tasks using GAI-networks
The enormous number of questions needed to acquire a full preference model when the size of the outcome space is large forces us to work with partial models that approximate the u...
Sérgio R. de M. Queiroz
SDM
2012
SIAM
294views Data Mining» more  SDM 2012»
11 years 10 months ago
Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
Tinghui Zhou, Hanhuai Shan, Arindam Banerjee, Guil...
CIKM
2008
Springer
13 years 9 months ago
SHOPSMART: product recommendations through technical specifications and user reviews
This paper describes a new method for providing recommendations tailored to a user's preferences using text mining techniques and online technical specifications of products....
Alexander Yates, James Joseph, Ana-Maria Popescu, ...
IIR
2010
13 years 9 months ago
Context-Dependent Recommendations with Items Splitting
Recommender systems are intelligent applications that help on-line users to tackle information overload by providing recommendations of relevant items. Collaborative Filtering (CF...
Linas Baltrunas, Francesco Ricci
DSS
2008
133views more  DSS 2008»
13 years 7 months ago
A semantic-expansion approach to personalized knowledge recommendation
The rapid propagation of the Internet and information technologies has changed the nature of many industries. Fast response and personalized recommendations have become natural tr...
Ting-Peng Liang, Yung-Fang Yang, Deng-Neng Chen, Y...