Natural Language Analysis for Semantic Document Modeling

To ease the retrieval of documents published on the Web, the documents should be classified in a way that users find helpful and meaningful. This paper presents an approach to semantic document classification and retrieval based on Natural Language Analysis and Conceptual Modeling. A conceptual domain model is used in combination with linguistic tools to define a controlled vocabulary for a document collection. Users may browse this domain model and interactively classify documents by selecting model fragments that describe the contents of the documents. Natural language tools are used to analyze the text of the documents and propose relevant model fragments in terms of selected domain model concepts and named relations. The fragments proposed are refined by the users and stored as document descriptions in RDF-XML format. For document retrieval, lexical analysis is used to pre-process search expressions and map these to the domain model for manual query-refinement. A prototype of the s...

• Type: Conference
• Year: 2000
• Where: NLDB
• Authors: Terje Brasethvik, Jon Atle Gulla
• Keywords: Document, Domain Model, Model Fragments, Natural Language Processing, NLDB 2000