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» Extending Jess to Handle Uncertainty
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EAAI
2007
90views more  EAAI 2007»
13 years 7 months ago
AI techniques in modelling, assignment, problem solving and optimization
This paper recapitulates the results of a long research on a family of artificial intelligence (AI) methods—relying on, e.g., artificial neural networks and search techniques...
Zsolt János Viharos, Zsolt Kemény
KAIS
2006
87views more  KAIS 2006»
13 years 7 months ago
Merging uncertain information with semantic heterogeneity in XML
Semi-structured information in XML can be merged in a logic-based framework [Hun02, Hun02b]. This framework has been extended to deal with uncertainty, in the form of probability ...
Anthony Hunter, Weiru Liu
ICDE
2009
IEEE
151views Database» more  ICDE 2009»
14 years 9 months ago
Decision Trees for Uncertain Data
Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information, which originates from...
Smith Tsang, Ben Kao, Kevin Y. Yip, Wai-Shing Ho, ...
ICPR
2006
IEEE
14 years 8 months ago
Type-2 Fuzzy Markov Random Fields to Handwritten Character Recognition
This paper integrates Markov random fields (MRFs) with type-2 fuzzy sets (T2 FSs) referred to as T2 FMRFs, which can handle the fuzziness of the labeling space as well as the rand...
Jia Zeng, Zhi-Qiang Liu
ER
2005
Springer
153views Database» more  ER 2005»
14 years 1 months ago
Automatically Grounding Semantically-Enriched Conceptual Models to Concrete Web Services
Abstract. The paper provides a conceptual framework for designing and executing business processes using semantic Web services. We envision a world in which a designer defines a ...
Eran Toch, Avigdor Gal, Dov Dori