Leveraging Metadata for Natural Language Processing

BOOM 2002

Abstract

Perhaps the single fastest way to locate information online, or in any large body of documents, is with a text search.  However, a pure text search is lacking in many regards.  Often documents are able to discuss topics while never directly stating them, or they will use slightly different terminology.  A pure text search will scan documents for the occurrence of words, but it will follow no particular logic or reason in the results it returns.

Recently XML and RDF have emerged to bring a semantic quality to information on the web.  While any human can look at a web page and immediately understand its semantics, XML and RDF are powerful because they provide semantic information that is understandable to machines.  This project uses XML metadata to improve searching accuracy in the form of an interactive chatbot that is both significantly more intelligent than a pure text search, and provides a more natural user experience.

Alexander Faaborg

Cornell University: BOOM 2002

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