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» Introduction to recommender systems
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KDD
2012
ACM
187views Data Mining» more  KDD 2012»
13 years 1 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
SDM
2012
SIAM
294views Data Mining» more  SDM 2012»
13 years 1 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...
SAC
2005
ACM
15 years 4 months ago
SVD-based collaborative filtering with privacy
Collaborative filtering (CF) techniques are becoming increasingly popular with the evolution of the Internet. Such techniques recommend products to customers using similar users...
Huseyin Polat, Wenliang Du
ECWEB
2010
Springer
219views ECommerce» more  ECWEB 2010»
15 years 1 days ago
Semantic Tag Cloud Generation via DBpedia
Abstract. Many current recommender systems exploit textual annotations (tags) provided by users to retrieve and suggest online contents. The text-based recommendation provided by t...
Roberto Mirizzi, Azzurra Ragone, Tommaso Di Noia, ...
CHI
1995
ACM
15 years 2 months ago
Social Information Filtering: Algorithms for Automating "Word of Mouth"
This paper describes a technique for making personalized recommendations from any type of database to a user based on similarities between the interest pro le of that user and tho...
Upendra Shardanand, Pattie Maes