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SUPPORTING DOMAIN SPECIFIC WEB-BASED SEARCH USING HEURISTIC KNOWLEDGE EXTRACTION

Modern search engines like Google support domain-independent search over the
vast information contained in web documents. However domain-specific information
access, such as finding less well-known people, locations, and events are not performed
efficiently without users developing sophisticated query strategies. This thesis describes
the design and development of an application to support one such domain-specific
information activity: for insurance (and related) companies to identify weather and
natural disaster damage to better assess when and where personnel will be needed. The
approach presented to supporting such activity combines information extraction with an
interactive presentation of results. Previous domain specific search engines extract
information about papers, people, and course information using rule-based or learningbased
techniques. However they use the results of information extraction in a typical
query and list of results interface. They fail to address the need for interaction based on
the extracted document features. The domain specific web-based search application
developed in this project combines information extraction with the interactive display of results to facilitate rapid information location. A heuristic evaluation was performed to
determine whether the application met the design goals and to improve the design.
Thus the final application has an unconventional but interactive presentation of
the results with the use of tree based display. The application also allows options for user
specific results caching and modification of the search and caching process. With a
heuristic based search process it extracts information about place, date and damages
regarding a specific disaster using a bank of search heuristics developed.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2008-08-55
Date16 January 2010
CreatorsGunanathan, Sudharsan
ContributorsShipman, Frank
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
TypeBook, Thesis, Electronic Thesis
Formatapplication/pdf

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