Thematic mapping - from unstructured documents to taxonomies

  • Authors:

  • Christina Yip Chung;Raymond Lieu;Jinhui Liu;Alpha Luk;Jianchang Mao;Prabhakar Raghavan

  • Affiliations:

  • Verity, Inc., Sunnyvale, CA;Verity, Inc., Sunnyvale, CA;Verity, Inc., Sunnyvale, CA;Verity, Inc., Sunnyvale, CA;Verity, Inc., Sunnyvale, CA;Verity, Inc., Sunnyvale, CA

  • Venue:
  • Proceedings of the eleventh international conference on Information and knowledge management
  • Year:
  • 2002

Quantified Score

Hi-index 0.00

Visualization

Abstract

Verity Inc. has developed a comprehensive suite of tools for accurately and efficiently organizing enterprise content which involves four basic steps: (i) creating taxonomies, (ii) building classification models, (iii) populating taxonomies with documents, and (iv) deploying populated taxonomies in enterprise portals. A taxonomy is a hierarchical representation of categories. A taxonomy provides a navigation structure for exploring and understanding the underlying corpus without sifting through a huge volume of documents. Thematic Mapping automatically discovers a concept tree from a corpus of unstructured documents and assigns meaningful labels to concepts based on a semantic network. Integrating with Verity Intelligent Classifier's user-friendly GUI, a user can drill down a concept tree for navigation, perform a conceptual search to retrieve documents pertaining to a concept, build a taxonomy from the concept tree, as well as edit a taxonomy to tailor it into various views (customized taxonomies) of the same corpus. Classification rules can be generated automatically from concepts. These classification rules can be used for populating documents into the taxonomy.