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ASUNAM
2010
IEEE
15 years 4 months ago
Mining Interaction Behaviors for Email Reply Order Prediction
—In email networks, user behaviors affect the way emails are sent and replied. While knowing these user behaviors can help to create more intelligent email services, there has no...
Byung-Won On, Ee-Peng Lim, Jing Jiang, Amruta Pura...
JAR
2007
85views more  JAR 2007»
15 years 5 months ago
User Interaction with the Matita Proof Assistant
Matita is a new, document-centric, tactic-based interactive theorem prover. This paper focuses on some of the distinctive features of the user interaction with Matita, characterize...
Andrea Asperti, Claudio Sacerdoti Coen, Enrico Tas...
PKDD
2007
Springer
196views Data Mining» more  PKDD 2007»
15 years 11 months ago
Speeding Up Feature Subset Selection Through Mutual Information Relevance Filtering
A relevance filter is proposed which removes features based on the mutual information between class labels and features. It is proven that both feature independence and class condi...
Gert Van Dijck, Marc M. Van Hulle
MHCI
2007
Springer
15 years 11 months ago
Incidental information and mobile search
There is much interest in providing effective mobile search tools. Our focus is the value of in situ sharing of users’ mobile search activity. The QnotA prototype displays other...
David Arter, George Buchanan, Matt Jones, Richard ...
162
Voted
WACV
2005
IEEE
15 years 11 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee