Foundations of statistical natural language processing
Foundations of statistical natural language processing
Data mining: concepts and techniques
Data mining: concepts and techniques
Measuring Similarity between Ontologies
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Clustering Ontology-Based Metadata in the Semantic Web
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Ontology Matching
OSS: a semantic similarity function based on hierarchical ontologies
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A comparative study of ontology based term similarity measures on PubMed document clustering
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Classification Analysis in Complex Online Social Networks Using Semantic Web Technologies
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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The main objectives of this paper is to propose a conceptual and software environment in which different aspects of cluster analysis of ontology-based data could be studied. The ontology-based dataset has two core components: description of categories and description of objects and relationships between them. Similarity between objects is defined as an amalgamation function of taxonomic, relationship and attribute similarity. The different measures to calculate similarity can be used. Further research is needed in order to evaluate these measures. The creation of a software tool which allows for classification of ontology-based data and comprehensive analysis of results is essential for the research in the area of ontology-based data mining. Such a tool should be universal, extensible and open. The universality manifests itself in the possibility of processing any data sets described by OWL tailored to meet individual requirements. The system extensibility means that it can be enriched with new elements without the necessity of making changes in its main elements. The openness enables the communications with other data analysis systems. In the paper theoretical aspects of cluster analysis of ontology-based data sets are presented. Next, a framework of cluster analysis system is outlined. Finally, some technical details of the system implementation are discussed.