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» Evaluating algorithms that learn from data streams
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ICASSP
2010
IEEE
15 years 7 months ago
Detecting local semantic concepts in environmental sounds using Markov model based clustering
Detecting the time of occurrence of an acoustic event (for instance, a cheer) embedded in a longer soundtrack is useful and important for applications such as search and retrieval...
Keansub Lee, Daniel P. W. Ellis, Alexander C. Loui
ACL
2011
14 years 11 months ago
Content Models with Attitude
We present a probabilistic topic model for jointly identifying properties and attributes of social media review snippets. Our model simultaneously learns a set of properties of a ...
Christina Sauper, Aria Haghighi, Regina Barzilay
KDD
2009
ACM
196views Data Mining» more  KDD 2009»
16 years 2 months ago
WhereNext: a location predictor on trajectory pattern mining
The pervasiveness of mobile devices and location based services is leading to an increasing volume of mobility data. This side effect provides the opportunity for innovative meth...
Anna Monreale, Fabio Pinelli, Roberto Trasarti, Fo...
WWW
2011
ACM
15 years 2 months ago
Semi-supervised truth discovery
Accessing online information from various data sources has become a necessary part of our everyday life. Unfortunately such information is not always trustworthy, as different sou...
Xiaoxin Yin, Wenzhao Tan
TMC
2010
139views more  TMC 2010»
15 years 6 months ago
Optimize Storage Placement in Sensor Networks
—Data storage has become an important issue in sensor networks as a large amount of collected data need to be archived for future information retrieval. Storage nodes are introdu...
Bo Sheng, Qun Li, Weizhen Mao