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125
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JASIS
2000
143views more  JASIS 2000»
15 years 2 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
ICML
2004
IEEE
16 years 3 months ago
Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
138
Voted
AGP
1997
IEEE
15 years 6 months ago
An Algorithm for Learning Abductive Rules
We propose an algorithm for learning abductive logic programs from examples. We consider the Abductive Concept Learning framework, an extension of the Inductive Logic Programming ...
Evelina Lamma, Paola Mello, Michela Milano, Fabriz...
97
Voted
JELIA
1990
Springer
15 years 6 months ago
Action Logic and Pure Induction
In Floyd-Hoare logic, programs are dynamic while assertions are static (hold at states). In action logic the two notions become one, with programs viewed as on-the-fly assertions ...
Vaughan R. Pratt
AIIA
2003
Springer
15 years 7 months ago
Incremental Induction of Rules for Document Image Understanding
This paper aims at presenting the application of first-order logic machine learning techniques to two document domains in order to learn rules for recognizing the semantic role of...
Stefano Ferilli, Nicola Di Mauro, Teresa Maria Alt...