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» Discovering Robust Knowledge from Dynamic Closed World Data
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AAAI
1996
13 years 5 months ago
Discovering Robust Knowledge from Dynamic Closed World Data
Many applications of knowledge discovery require the knowledge to be consistent with data. Examples include discovering rules for query optimization, database integration, decisio...
Chun-Nan Hsu, Craig A. Knoblock
IJCAI
1989
13 years 5 months ago
Building a World Model for a Mobile Robot Using Dynamic Semantic Constraints
We are developing a new paradigm for a world model construction system which interprets a scene and builds a world model for a mobile robot using dynamic semantic constraints. The...
Minoru Asada, Yoshiaki Shirai
DATAMINE
2006
130views more  DATAMINE 2006»
13 years 4 months ago
Mining Adaptive Ratio Rules from Distributed Data Sources
Different from traditional association-rule mining, a new paradigm called Ratio Rule (RR) was proposed recently. Ratio rules are aimed at capturing the quantitative association kno...
Jun Yan, Ning Liu, Qiang Yang, Benyu Zhang, QianSh...
IEAAIE
2009
Springer
13 years 11 months ago
Incremental Mining of Ontological Association Rules in Evolving Environments
The process of knowledge discovery from databases is a knowledge intensive, highly user-oriented practice, thus has recently heralded the development of ontology-incorporated data ...
Ming-Cheng Tseng, Wen-Yang Lin
SC
2005
ACM
13 years 10 months ago
PerfExplorer: A Performance Data Mining Framework For Large-Scale Parallel Computing
Parallel applications running on high-end computer systems manifest a complexity of performance phenomena. Tools to observe parallel performance attempt to capture these phenomena...
Kevin A. Huck, Allen D. Malony