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  • DataMiningGrid Text Mining and Ontology-learning Services

Text mining is a technology that is becoming increasingly important for today’s and tomorrow’s distributed knowledge workers in a wide range of domains. The project will develop text mining and ontology-learning services and interfaces. Emphasis will be placed on developing grid-enabled algorithms for text mining and automated learning of ontologies. They are implemented on top of the generic grid data mining facilities and highlight the solution potential of the DataMiningGrid environment.

Text mining and ontology-learninig seervices and interfaces will be developed under workpackage 4 (WP4) of the project. While WP3 aims at developing generic analysis services, WP4 develops specific applications based on real-world use cases to show and evaluate the usefulness of the generic framework. The methods developed in WP4 will be tested in real-world applications, whereas the realized demonstrators for these methods will be shown on public data.

The generic services and tools developed in WP3 can be used as primitives for more specialized data mining approaches. As a proof-of-concept for the validity of the generic design, a variety of cutting-edge methods will be designed, grid enabled and implemented on top of the framework. These methods will cover a broad range of knowledge grid services, so that the potential of data mining can be assessed on a sufficiently large sample. The methods to be developed focus on

  • distributed text mining,
  • automatic ontology construction, and
  • distributed structured Kernel methods for bioinformatics.

Updated on January 12, 2005