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  • MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, an...
    MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
    to classification java learning machine model nlp toolkit topic by pitman and 2 other users on Nov 12, 2008, 6:32 AM
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  • EDUCAUSE is a nonprofit association whose mission is to advance higher education by promoting the intelligent use of information technology.
    to academic community education learning resources technology by pitman and 6 other users on Oct 7, 2008, 9:14 PM
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  • Weka-related Projects (WekaWiki) List of resources.
    to Open data java learning list mining open resources software source by pitman and 1 other user on Jan 25, 2008, 12:03 AM
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  • [Knowledge and Data Engineering Group] [Department of Electrical Engineering/Computer Science] [University of Kassel, Kassel, Germany] Home Teachin...
    [Knowledge and Data Engineering Group] [Department of Electrical Engineering/Computer Science] [University of Kassel, Kassel, Germany] Home Teaching Research Publications Master Theses Contact Me Project Links Business Other eMail Me © Andreas Hotho, 2007 function: Scientific Assistant current project: KDUbiq, Tagora, Nepomuk, DataProcess research interest: Folksonomy and Web 2.0 -- Text Clustering with background knowledge -- Text Mining -- Data Mining -- Ontology Learning -- Semantic Web Mining and related issues consulting for students: eMail Me BibSonomy BibSonomy, our bookmark and publication sharing system
    to bibsonomy data engineering homepage knowledge learning mining by pitman and 8 other users on Jan 18, 2008, 9:32 PM
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  • Designing and refining ontologies becomes a tedious task, once the boundary to real-world-size knowledge bases has been crossed. Hence semi-automatic metho...
    Designing and refining ontologies becomes a tedious task, once the boundary to real-world-size knowledge bases has been crossed. Hence semi-automatic methods supporting those tasks will determine the future success of ontologies in practice. Our research therefore aims at the conceptual development and implementation of tools for semi-automatic ontology engineering. By combining Ontology Learning and Relational Exploration we hope to overcome the knowledge acquisition bottleneck, especially with respect to expressive axiomatizations (see our seminal paper at ICCS'2007). The RELExO framework supporting the refinement and evaluation of OWL DL ontologies is open source and publicly available under the LGPL license.
    to exploration learning ml ontology relational by pitman and 1 other user on Jan 10, 2008, 1:16 AM
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publications

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