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» Mining Frequency Pattern from Mobile Users
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137
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GIS
2007
ACM
15 years 10 months ago
Predicting future locations using clusters' centroids
As technology advances we encounter more available data on moving objects, thus increasing our ability to mine spatiotemporal data. We can use this data for learning moving object...
Sigal Elnekave, Mark Last, Oded Maimon
138
Voted
WECWIS
2002
IEEE
131views ECommerce» more  WECWIS 2002»
15 years 8 months ago
Mining Client-Side Activity for Personalization
“Garbage in. garbage out” is a well-known phrase in computer analysis, and one that comes to mind when mining Web data to draw conclusions about Web users. The challenge is th...
Kurt D. Fenstermacher, Mark Ginsburg
175
Voted
KDD
2012
ACM
212views Data Mining» more  KDD 2012»
13 years 6 months ago
Harnessing the wisdom of the crowds for accurate web page clipping
Clipping Web pages, namely extracting the informative clips (areas) from Web pages, has many applications, such as Web printing and e-reading on small handheld devices. Although m...
Lei Zhang, Linpeng Tang, Ping Luo, Enhong Chen, Li...
KDD
1999
ACM
117views Data Mining» more  KDD 1999»
15 years 8 months ago
Identifying Distinctive Subsequences in Multivariate Time Series by Clustering
Most time series comparison algorithms attempt to discover what the members of a set of time series have in common. We investigate a di erent problem, determining what distinguish...
Tim Oates
145
Voted
KDD
2001
ACM
262views Data Mining» more  KDD 2001»
16 years 4 months ago
LOGML: Log Markup Language for Web Usage Mining
Web Usage Mining refers to the discovery of interesting information from user navigational behavior as stored in web access logs. While extracting simple information from web logs...
John R. Punin, Mukkai S. Krishnamoorthy, Mohammed ...