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Grant: Discovery Grants Program - Individual

University of Regina

$28,000.00

Granular Computing and Its Applications in Information Retrieval Support Systems

EF 2012-13

Résumé
Granular computing explores multiple levels of granularity in thinking, problem solving, and information processing. It uses a hierarchical granular structure consisting of a family of integrative levels. A level consists of inter-connected and inter-acting granules of the same granularity or nature. A granule is a focal point used in an observation or a unit used in a discussion during problem solving, giving a local and partial description. The granules in a level collectively provide a global and complete description. A family of granular structures provides multiple views of the same problem. A central thesis of my research is a triarchic theory of granular computing encompassing the three perspectives of philosophical foundations, methodological foundations, and computational paradigms. It stresses a structured understanding of, and structured methods for solving, a real-world problem from multiple views and at multiple levels of abstraction within each view. The proposed research program aims to fully develop the triarchic theory by formulating and articulating granular computing ideas and to fully capitalize on them in the areas of human problem solving and intelligent systems. By examining and synthesizing results from existing studies, we plan to design a language for describing precisely multilevel granular structures, to formulate a set of general discipline-independent principles and mechanisms for understanding problem solving using granular structures, and to construct and compile a set of granular computing algorithms, including top-down, bottom-up, middle-out and progressive computing. An understanding of the underlying granule-based principles of human problem solving can be used to instruct and empower more people to be better at solving problems. The same principles can also be applied in designing intelligent systems with human-level intelligence. Concrete models, such as rough sets, formal concept analysis, and knowledge spaces, will be carefully investigated. Prototype information retrieval support systems will be implemented by exploring granular structures of individual documents, a document space, a user space, and a domain knowledge space.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Saskatchewan, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
137766-2012
Name nom
Yao, Yiyu
Department département
Computer Science
Organization id
17
Institution établissement
University of Regina
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2012
Competition year année de concours
2012
Award amount
28000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
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
5
Application title
Granular Computing and Its Applications in Information Retrieval Support Systems
Keyword
NSERC
Application summary
Granular computing explores multiple levels of granularity in thinking, problem solving, and information processing. It uses a hierarchical granular structure consisting of a family of integrative levels. A level consists of inter-connected and inter-acting granules of the same granularity or nature. A granule is a focal point used in an observation or a unit used in a discussion during problem solving, giving a local and partial description. The granules in a level collectively provide a global and complete description. A family of granular structures provides multiple views of the same problem. A central thesis of my research is a triarchic theory of granular computing encompassing the three perspectives of philosophical foundations, methodological foundations, and computational paradigms. It stresses a structured understanding of, and structured methods for solving, a real-world problem from multiple views and at multiple levels of abstraction within each view. The proposed research program aims to fully develop the triarchic theory by formulating and articulating granular computing ideas and to fully capitalize on them in the areas of human problem solving and intelligent systems. By examining and synthesizing results from existing studies, we plan to design a language for describing precisely multilevel granular structures, to formulate a set of general discipline-independent principles and mechanisms for understanding problem solving using granular structures, and to construct and compile a set of granular computing algorithms, including top-down, bottom-up, middle-out and progressive computing. An understanding of the underlying granule-based principles of human problem solving can be used to instruct and empower more people to be better at solving problems. The same principles can also be applied in designing intelligent systems with human-level intelligence. Concrete models, such as rough sets, formal concept analysis, and knowledge spaces, will be carefully investigated. Prototype information retrieval support systems will be implemented by exploring granular structures of individual documents, a document space, a user space, and a domain knowledge space.