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ML
2006
ACM
142views Machine Learning» more  ML 2006»
14 years 9 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
SIGIR
2004
ACM
15 years 3 months ago
A study of methods for normalizing user ratings in collaborative filtering
The goal of collaborative filtering is to make recommendations for a test user by utilizing the rating information of users who share interests similar to the test user. Because r...
Rong Jin, Luo Si
CIKM
2001
Springer
15 years 2 months ago
Merging Techniques for Performing Data Fusion on the Web
Data fusion on the Web refers to the merging, into a unified single list, of the ranked document lists, which are retrieved in response to a user query by more than one Web search...
Theodora Tsikrika, Mounia Lalmas
CIKM
2008
Springer
14 years 12 months ago
Book search: indexing the valuable parts
With massive book digitization efforts underway, there is a need for developing effective book retrieval strategies. This paper explores the relative contribution of different par...
Walid Magdy, Kareem Darwish
CHI
2007
ACM
15 years 10 months ago
The role of choice and customization on users' interaction with embodied conversational agents: effects on perception and perfor
We performed an empirical study exploring people's interactions with an embodied conversational agent (ECA) while performing two tasks. Conditions varied with respect to 1) w...
Jun Xiao, John T. Stasko, Richard Catrambone