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DPD
2002
125views more  DPD 2002»
13 years 10 months ago
Parallel Mining of Outliers in Large Database
Data mining is a new, important and fast growing database application. Outlier (exception) detection is one kind of data mining, which can be applied in a variety of areas like mon...
Edward Hung, David Wai-Lok Cheung
KDD
2010
ACM
247views Data Mining» more  KDD 2010»
14 years 5 days ago
Metric forensics: a multi-level approach for mining volatile graphs
Advances in data collection and storage capacity have made it increasingly possible to collect highly volatile graph data for analysis. Existing graph analysis techniques are not ...
Keith Henderson, Tina Eliassi-Rad, Christos Falout...
SIGECOM
2003
ACM
174views ECommerce» more  SIGECOM 2003»
14 years 3 months ago
Collaboration software to reduce inventory and increase response
Some recent trends in business and manufacturing hold the promise of greater profits, yet, due to profit-robbing inventory increases, this promise has not been fully realized. [9]...
Indu Bingham, Barbara Hoefle, Kim Phan, Jim Sizemo...
PAKDD
2009
ACM
135views Data Mining» more  PAKDD 2009»
14 years 5 months ago
On Mining Rating Dependencies in Online Collaborative Rating Networks
The trend of social information processing sees e-commerce and social web applications increasingly relying on user-generated content, such as rating, to determine the quality of o...
Hady Wirawan Lauw, Ee-Peng Lim, Ke Wang
ICDM
2006
IEEE
161views Data Mining» more  ICDM 2006»
14 years 4 months ago
Personalization in Context: Does Context Matter When Building Personalized Customer Models?
The idea that context is important when predicting customer behavior has been maintained by scholars in marketing and data mining. However, no systematic study measuring how much ...
Michele Gorgoglione, Cosimo Palmisano, Alexander T...