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BCSHCI
2007
10 years 12 months ago
"The devil you know knows best": how online recommendations can benefit from social networking
The defining characteristic of the Internet today is an abundance of information and choice. Recommender Systems (RS), designed to alleviate this problem, have so far not been ver...
Philip Bonhard, Martina Angela Sasse, Clare Harrie...
ESWS
2008
Springer
11 years 8 days ago
Semantic Reasoning: A Path to New Possibilities of Personalization
Abstract. Recommender systems face up to current information overload by selecting automatically items that match the personal preferences of each user. The so-called content-based...
Yolanda Blanco-Fernández, José J. Pa...
CIKM
2008
Springer
11 years 15 days ago
SoRec: social recommendation using probabilistic matrix factorization
Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King
CCS
2010
ACM
11 years 1 months ago
Towards publishing recommendation data with predictive anonymization
Recommender systems are used to predict user preferences for products or services. In order to seek better prediction techniques, data owners of recommender systems such as Netfli...
Chih-Cheng Chang, Brian Thompson, Hui (Wendy) Wang...
EWCBR
2006
Springer
11 years 2 months ago
Combining Case-Based and Similarity-Based Product Recommendation
Product recommender systems are a popular application and research field of CBR for several years now. However, almost all CBRbased recommender systems are not case-based in the or...
Armin Stahl
ETRICS
2006
11 years 2 months ago
Do You Trust Your Recommendations? An Exploration of Security and Privacy Issues in Recommender Systems
Recommender systems are widely used to help deal with the problem of information overload. However, recommenders raise serious privacy and security issues. The personal information...
Shyong K. Lam, Dan Frankowski, John Riedl
COOPIS
2004
IEEE
11 years 2 months ago
Paradigms for Decentralized Social Filtering Exploiting Trust Network Structure
Recommender systems, notably collaborative and hybrid information filtering approaches, vitally depend on neighborhood formation, i.e., selecting small subsets of most relevant pee...
Cai-Nicolas Ziegler, Georg Lausen
COOPIS
2004
IEEE
11 years 2 months ago
Trust-Aware Collaborative Filtering for Recommender Systems
Recommender Systems allow people to find the resources they need by making use of the experiences and opinions of their nearest neighbours. Costly annotations by experts are replac...
Paolo Massa, Paolo Avesani
CIKM
2004
Springer
11 years 2 months ago
Taxonomy-driven computation of product recommendations
Recommender systems have been subject to an enormous rise in popularity and research interest over the last ten years. At the same time, very large taxonomies for product classifi...
Cai-Nicolas Ziegler, Georg Lausen, Lars Schmidt-Th...
SIGIR
2010
ACM
11 years 2 months ago
Temporal diversity in recommender systems
Collaborative Filtering (CF) algorithms, used to build webbased recommender systems, are often evaluated in terms of how accurately they predict user ratings. However, current eva...
Neal Lathia, Stephen Hailes, Licia Capra, Xavier A...
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