A Free-text Database Retrieval System Incorporating The Semantic Network Wordnet

Award Information
Agency:
Department of Defense
Branch
Defense Advanced Research Projects Agency
Amount:
$49,990.00
Award Year:
1993
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Agency Tracking Number:
19745
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Netrologic, Inc.
5080 Shoreham Place, Suite, 201, San Diego, CA, 92122
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Sue Toledo
(619) 587-0970
Business Contact:
() -
Research Institution:
n/a
Abstract
Searches of free text databases depend on the keywords used in the request for information. If keywords are extracted from the user's query and no use is made of synonyms, relevant data in the database may be overlooked. The same can be the case if class-subclass, and part-whole information is ignored. The semantic network WordNet that has been developed a Princeton University encodes a very rich store of semantic information concerning relationships between words that are used constantly in any language understanding. These include subordinate-superordinate and part-whole information, as well as refinements to them, restrictions of relationships to appropriate contexts and mappings between words of different categories (nouns, adjectives, verbs). It is envisioned that uses of the relationships encoded in WordNet can allow the computer to make deductions allowing it to determine that many texts are relevant to the needs that a user expressed in quite different terms. Netrologic proposes to develop a system to categorize articles based on concepts encoded in WordNet, and to create a free text database interface to search documents categorized in this way. ANTICIPATED BENEFITS: The efficient determination of all documents in a database relevant to a user's needs is becoming increasingly important, as larger and larger free text databases are coming in line. A system that contains an embedded semantic network can be an invaluable aid to everyone in both government and the general public who will be making extensive uses of large databases.

* information listed above is at the time of submission.

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