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» Improved Recommendations via (More) Collaboration
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WEBDB
2010
Springer
171views Database» more  WEBDB 2010»
10 years 28 days ago
Improved Recommendations via (More) Collaboration
We consider in this paper a popular class of recommender systems that are based on Collaborative Filtering (CF for short). CF is the process of predicting customer ratings to item...
Rubi Boim, Haim Kaplan, Tova Milo, Ronitt Rubinfel...
IUI
2003
ACM
10 years 1 months ago
Towards more conversational and collaborative recommender systems
Current recommender systems, based on collaborative filtering, implement a rather limited model of interaction. These systems intelligently elicit information from a user only dur...
Giuseppe Carenini, Jocelyin Smith, David Poole
CHI
2006
ACM
10 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...
ICDM
2010
IEEE
267views Data Mining» more  ICDM 2010»
9 years 5 months ago
Personalizing Web Page Recommendation via Collaborative Filtering and Topic-Aware Markov Model
Web-page recommendation is to predict the next request of pages that Web users are potentially interested in when surfing the Web. This technique can guide Web users to find more u...
Qingyan Yang, Ju Fan, Jianyong Wang, Lizhu Zhou
WSDM
2016
ACM
126views Data Mining» more  WSDM 2016»
4 years 3 months ago
CCCF: Improving Collaborative Filtering via Scalable User-Item Co-Clustering
Collaborative Filtering (CF) is the most popular method for recommender systems. The principal idea of CF is that users might be interested in items that are favorited by similar ...
Yao Wu, Xudong Liu, Min Xie, Martin Ester, Qing Ya...
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