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MOBICOM
2010
ACM
13 years 9 months ago
Profiling users in a 3g network using hourglass co-clustering
With widespread popularity of smart phones, more and more users are accessing the Internet on the go. Understanding mobile user browsing behavior is of great significance for seve...
Ram Keralapura, Antonio Nucci, Zhi-Li Zhang, Lixin...
ICTAI
2006
IEEE
14 years 2 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...
CIKM
2005
Springer
14 years 2 months ago
Opportunity map: a visualization framework for fast identification of actionable knowledge
Data mining techniques frequently find a large number of patterns or rules, which make it very difficult for a human analyst to interpret the results and to find the truly interes...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Weimin Xia...
EEE
2004
IEEE
14 years 14 days ago
Mining Traveling and Purchasing Behaviors of Customers in Electronic Commerce Environment
Web usage mining is the process of extracting interesting patterns from web logs. This paper proposes an IPA (Integrating Path traversal patterns and Association rules) model for ...
Yue-Shi Lee, Show-Jane Yen, Ghi-Hua Tu, Min-Chi Hs...
CORR
2010
Springer
173views Education» more  CORR 2010»
13 years 6 months ago
Mining Multi-Level Frequent Itemsets under Constraints
Mining association rules is a task of data mining, which extracts knowledge in the form of significant implication relation of useful items (objects) from a database. Mining multi...
Mohamed Salah Gouider, Amine Farhat