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» Predicting user interests from contextual information
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SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
13 years 4 days ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
ICTAI
2006
IEEE
15 years 3 months ago
Learning to Predict Salient Regions from Disjoint and Skewed Training Sets
We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
SIGIR
2006
ACM
15 years 3 months ago
Learning user interaction models for predicting web search result preferences
Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of ...
Eugene Agichtein, Eric Brill, Susan T. Dumais, Rob...
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SIGCOMM
2009
ACM
15 years 4 months ago
SMS-based contextual web search
SMS-based web search is different from traditional web search in that the final response to a search query is limited to a very small number of bytes (typically 1-2 SMS messages...
Jay Chen, Brendan Linn, Lakshminarayanan Subramani...
WIRI
2005
IEEE
15 years 3 months ago
Collaborative Filtering by Mining Association Rules from User Access Sequences
Recent research in mining user access patterns for predicting Web page requests focuses only on consecutive sequential Web page accesses, i.e., pages which are accessed by followi...
Mei-Ling Shyu, Choochart Haruechaiyasak, Shu-Ching...