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RECSYS
2009
ACM
11 years 4 months ago
Regret-based optimal recommendation sets in conversational recommender systems
Current conversational recommender systems are unable to offer guarantees on the quality of their recommendations due to a lack of principled user utility models. We develop an ap...
Paolo Viappiani, Craig Boutilier
UM
2009
Springer
11 years 4 months ago
How Users Perceive and Appraise Personalized Recommendations
Abstract. Traditional websites have long relied on users revealing their preferences explicitly through direct manipulation interfaces. However recent recommender systems have gone...
Nicolas Jones, Pearl Pu, Li Chen
UM
2009
Springer
11 years 4 months ago
What Have the Neighbours Ever Done for Us? A Collaborative Filtering Perspective
Collaborative filtering (CF) techniques have proved to be a powerful and popular component of modern recommender systems. Common approaches such as user-based and item-based metho...
Rachael Rafter, Michael P. O'Mahony, Neil J. Hurle...
CSE
2009
IEEE
11 years 5 months ago
TagRec: Leveraging Tagging Wisdom for Recommendation
—Due to the exponential growth of information on the Web, Recommender Systems have been developed to generate suggestions to help users overcome information overload and sift thr...
Tom Chao Zhou, Hao Ma, Irwin King, Michael R. Lyu
WWW
2009
ACM
11 years 5 months ago
Tagommenders: connecting users to items through tags
Tagging has emerged as a powerful mechanism that enables users to find, organize, and understand online entities. Recommender systems similarly enable users to efficiently navig...
Shilad Sen, Jesse Vig, John Riedl
KDD
2002
ACM
196views Data Mining» more  KDD 2002»
11 years 10 months ago
Comparing Two Recommender Algorithms with the Help of Recommendations by Peers
Abstract. Since more and more Web sites, especially sites of retailers, offer automatic recommendation services using Web usage mining, evaluation of recommender algorithms has bec...
Andreas Geyer-Schulz, Michael Hahsler
KDD
2006
ACM
200views Data Mining» more  KDD 2006»
11 years 10 months ago
A Random-Walk Based Scoring Algorithm Applied to Recommender Engines
Recommender systems are an emerging technology that helps consumers find interesting products and useful resources. A recommender system makes personalized product suggestions by e...
Augusto Pucci, Marco Gori, Marco Maggini
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
11 years 10 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
WWW
2004
ACM
11 years 11 months ago
Shilling recommender systems for fun and profit
Recommender systems have emerged in the past several years as an effective way to help people cope with the problem of information overload. One application in which they have bec...
Shyong K. Lam, John Riedl
WWW
2009
ACM
11 years 11 months ago
Personalized recommendation on dynamic content using predictive bilinear models
In Web-based services of dynamic content (such as news articles), recommender systems face the difficulty of timely identifying new items of high-quality and providing recommendat...
Wei Chu, Seung-Taek Park
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