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IASSE
2004
15 years 7 months ago
A Model for Multi-relational Data Mining on Demand Forecasting
Accurate demand forecasting remains difficult and challenging in today's competitive and dynamic business environment, but even a little improvement in demand prediction may ...
Qin Ding, Bhavin Parikh
CINQ
2004
Springer
189views Database» more  CINQ 2004»
15 years 12 months ago
Employing Inductive Databases in Concrete Applications
In this paper we present the application of the inductive database approach to two practical analytical case studies: Web usage mining in Web logs and financial data. As far as co...
Rosa Meo, Pier Luca Lanzi, Maristella Matera, Dani...
JASIS
2000
143views more  JASIS 2000»
15 years 6 months ago
Discovering knowledge from noisy databases using genetic programming
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Man Leung Wong, Kwong-Sak Leung, Jack C. Y. Cheng
MOBIDE
2010
ACM
15 years 6 months ago
Using data mining to handle missing data in multi-hop sensor network applications
A sensor's data loss or corruption, aka sensor data missing, is a common phenomenon in modern wireless sensor networks. It is more severe for multi-hop sensor network (MSN) a...
Le Gruenwald, Hanqing Yang, Md. Shiblee Sadik, Rah...
VLDB
1997
ACM
175views Database» more  VLDB 1997»
15 years 10 months ago
STING: A Statistical Information Grid Approach to Spatial Data Mining
Spatial data mining, i.e., discovery of interesting characteristics and patterns that may implicitly exist in spatial databases, is a challenging task due to the huge amounts of s...
Wei Wang 0010, Jiong Yang, Richard R. Muntz