Lp, a logic for representing and reasoning with statistical knowledge
Computational Intelligence
Commonality-Based ABox Retrieval
Commonality-Based ABox Retrieval
Assessing semantic similarity among spatial entity classes
Assessing semantic similarity among spatial entity classes
A dissimilarity measure for ALC concept descriptions
Proceedings of the 2006 ACM symposium on Applied computing
The Description Logic Handbook
The Description Logic Handbook
Resolution-Based approximate reasoning for OWL DL
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Principles of inductive reasoning on the semantic web: a framework for learning in AL-log
PPSWR'05 Proceedings of the Third international conference on Principles and Practice of Semantic Web Reasoning
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This work presents a method founded on instance-based learning algorithms for inductive (memory-based) reasoning on ABoxes. The method, which exploits a semantic dissimilarity measure between concepts and instances, can be employed both to infer class membership of instances and to predict hidden assertions that are not logically entailed from the knowledge base and need to be successively validated by humans (e.g. a knowledge engineer or a domain expert). In the experimentation, we show that the method can effectively help populating an ontology with likely assertions that could not be logically derived.