Contextual Spelling Suggestions Based on Specialized Vocabulary and Statistical Information of Historical System Usage

Award Information
Agency:
Department of Energy
Branch
n/a
Amount:
$100,000.00
Award Year:
2007
Program:
SBIR
Phase:
Phase I
Contract:
DE-FG02-07ER84707
Award Id:
84128
Agency Tracking Number:
82166
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
1155 Commerce Park Drive, Oak Ridge, TN, 37831
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
804891851
Principal Investigator:
MarkMartin
Mr
(865) 576-2097
markmartin@iiaweb.com
Business Contact:
FrancielAzpurua
Ms
(865) 298-1228
Franciel@iiaweb.com
Research Institute:
n/a
Abstract
Today¿s general purpose search engines have developed contextual based spelling/search suggestion software tools that are derived from the historical usage of the system. In other words, every search the system performs is stored and used as the basis of a statistical algorithm that locates contextual errors in a search. In the past several years, research analysts have identified a new tier of search called ¿specialized search,¿ which includes local, topical, and vertical searches. Vertical search engines, such as the DOE Office of Scientific and Technical Information¿s Information Bridge and Energy Citations Database, have not had the same success with the application of spelling/search suggestion due to the lower total population of searches performed against these sources. This project will develop a non-contextua,l pure spelling suggestion tool based on common spelling correction algorithms driven by word lists to be used with vertical search engines. Phase I will create a prototype spelling/search suggestion Web-based XML tool that combines historical usage and specialized vocabulary to contextually correct spelling or other search problems. Phase II will build upon the experimental data acquired from the prototype service, in order to develop a more robust Application Program Interface (API) tool and a more mature algorithm to create suggestions. Commercial Applications and other Benefits as described by the awardee: As vertical search engines gain popularity, the new tool should improve specialized search efficiency and effectiveness. Future benefits should include automation of historical data and specialized vocabulary building, thereby optimizing specialized searching for researchers, scientists, professionals, and academics.

* information listed above is at the time of submission.

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