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Grant: Research Tools and Instruments - Category 1 (<$150,000)

York University

$47,512.00

Context-aware information retrieval and semantic text analysis for very large unstructured data

EF 2007-08

Résumé
With the ever-increasing large amount of digital information available, the need for advanced Information Retrieval (IR) and text analysis systems increases. This wealth of digital information presents a major data-analysis challenge for us. How to manipulate, analyze and understand large quantities of complex data becomes extremely important.Our primary goal of this proposed research is to develop more advanced and novel tools in information technology to search for the most relevant information and discover significant patterns from very large unstructured data. In particular, (1) we will establish an Information Retrieval and Text Analysis Research Lab (IRLab); (2) we will build a context-aware search engine to filter out unnecessary information and implement semantic text analysis tools to effectively extract key elements from free-form unstructured data for improving retrieval performance.The proposed research will lead to more effective information retrieval applications in many domains such as medical health care, Web search, business enterprise search and bioinformatics, which will bring broad benefits to society and people from both academia and industry.
Programme
Research Tools and Instruments - Category 1 (<$150,000)
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
359136-2008
Name nom
Huang, Xiangji(Jimmy)
Department département
Information Technology, School of
Organization id
38
Institution établissement
York University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2007
Competition year année de concours
2008
Award amount
47512
Program id
EQPEQ
Program name en
Research Tools and Instruments - Category 1 (<$150,000)
Program name fr
Outils et instruments de recherche - catégorie 1 (<150 000$)
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
330
Committee name en
Computing and Information Sciences - A
Committee name fr
Informatique - A
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2700
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Information technology
Research subject fr
Technologie de l'information
Partie
1
Nb partie
1
Application title
Context-aware information retrieval and semantic text analysis for very large unstructured data
Keyword
NA
Application summary
With the ever-increasing large amount of digital information available, the need for advanced Information Retrieval (IR) and text analysis systems increases. This wealth of digital information presents a major data-analysis challenge for us. How to manipulate, analyze and understand large quantities of complex data becomes extremely important.Our primary goal of this proposed research is to develop more advanced and novel tools in information technology to search for the most relevant information and discover significant patterns from very large unstructured data. In particular, (1) we will establish an Information Retrieval and Text Analysis Research Lab (IRLab); (2) we will build a context-aware search engine to filter out unnecessary information and implement semantic text analysis tools to effectively extract key elements from free-form unstructured data for improving retrieval performance.The proposed research will lead to more effective information retrieval applications in many domains such as medical health care, Web search, business enterprise search and bioinformatics, which will bring broad benefits to society and people from both academia and industry.