Knowledgeincorporated intelligent solving methodsare prevailing in practical planningandschedulingbecauseof the large problemsize and complexconstraints. However,when intelligent ...
Setsuo Tsuruta, Takashi Onoyama, Sen Kubota, Kazuk...
Traditional benchmarking methods for information retrieval (IR) are based on experimental performance evaluation. Although the metrics precision and recall can measure the perform...
Dawei Song, Kam-Fai Wong, Peter Bruza, Chun Hung C...
This paper discusses the empirical evaluation of improving generalization performance of neural networks by systematic treatment of training and test failures. As a result of syst...
Qualitative probabilistic networks have been designed for probabilistic reasoning in a qualitative way. As a consequence of their coarse level of representation detail, qualitativ...
Silja Renooij, Linda C. van der Gaag, Shaw Green, ...
Bayesian KnowledgeBases (BKB)are a rule-based probabilistic modelthat extend BayesNetworks(BN), by allowing context-sensitive independenceand cycles in the directed graph. BKBshav...
Extracting knowledge from existing sources of information is a key development area to unlock previously unknown relationships between specific data points. Data mining is a techn...
In the first section wegive a very short surveyon current researchon web-basededucationalsystemsand relatedproblems.Inthesecondsectionwearguethat knowledgerepresentationandontolog...
Christoph Peylo, Wilfried Teiken, Claus-Rainer Rol...