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Mixed-Initiative Clustering.pdf

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Preview of Mixed-Initiative Clustering
🔗 Source: cs.cmu.edu
📊 Size: 1.42 MB
📄 Pages: 118 pages
⬇️ Downloads: 102

Summary

Mixed-initiative clustering is a collaborative task between a user and a machine to analyze a large set of documents, with the hypothesis that both can learn better clustering models through interactive learning and communication. This thesis provides a framework for mixed-initiative clustering, consisting of machine learning and teaching phases, and user learning and teaching phases, and demonstrates its effectiveness through several built systems and user studies, showing advantages over non-mixed-initiative approaches in learning and teaching ontologies.

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Description

Mixed-initiative clustering is a collaborative task between a user and a machine to analyze a large set of documents, with the hypothesis that both can learn...

Technical Information

  • File Format: PDF
  • File Size: 1.42 MB
  • Pages: 118
  • Language: EN
  • Total Downloads: 102
  • Last Updated: 1 week ago

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This PDF document about Mixed-Initiative Clustering provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Mixed-Initiative Clustering.

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