Published: 2004 August
Bemerkung: located at the 10th International ACM SIGKDD Conference on Knowledge Discovery and Data Mining KDD 2004, 22nd August 2004 - Seattle, WA, USA
The intention of the workshop is to bring together researchers from the two research areas Semantic Web and Knowledge Discovery. According to T. Berners-Lee the Semantic Web is "an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation". Current standardization efforts include e.g. the W3C recommendation for the Web Ontology Language (OWL). Knowledge Discovery is defined by U.M. Fayyad as "the nontrivial process of identifying valid, previously unknown, potentially useful patterns in data". We foresee two ways of combining these areas. On the one hand, mining for the semantic web includes the application of knowledge discovery methods and techniques to support the setting up of the semantic web itself. Prominent examples are here ontology learning and population of ontologies (instance learning). On the other hand, mining from the semantic web emphasizes the usage of semantic web technologies for mining purposes such as e.g. the usage of taxonomies in recommender systems, applying association rules with generalizations or clustering with background knowledge in form of ontologies.
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Maschinelles Lernen, Ontology Learning, Semantic Web