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RECSYS
2009
ACM
13 years 11 months ago
Using a trust network to improve top-N recommendation
Top-N item recommendation is one of the important tasks of recommenders. Collaborative filtering is the most popular approach to building recommender systems which can predict ra...
Mohsen Jamali, Martin Ester
RECSYS
2009
ACM
13 years 11 months ago
Applying relevant set correlation clustering to multi-criteria recommender systems
This thesis investigates application of clustering to multi-criteria ratings as a method of improving the precision of top-N recommendations. With the advent of ecommerce sites th...
Nkechi Nnadi
IUI
2009
ACM
14 years 1 months ago
Tagsplanations: explaining recommendations using tags
While recommender systems tell users what items they might like, explanations of recommendations reveal why they might like them. Explanations provide many benefits, from improvi...
Jesse Vig, Shilad Sen, John Riedl
WWW
2009
ACM
14 years 5 months ago
Towards context-aware search by learning a very large variable length hidden markov model from search logs
Capturing the context of a user's query from the previous queries and clicks in the same session may help understand the user's information need. A context-aware approac...
Huanhuan Cao, Daxin Jiang, Jian Pei, Enhong Chen, ...
ICFP
2006
ACM
14 years 4 months ago
Towards an automatic complexity analysis for generic programs
Generic libraries, such as the C++ Standard Template Library (STL), provide flexible, high-performance algorithms and data types, along with functional specifications and performa...
Kyle D. Ross