Research Article

Semantic Information Retrieval Model: Fuzzy Ontology Approach

by  Zeinab E. Attia, Ahmed M. Gadallah, Hesham A. Hefny
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Issue 13
Published: April 2014
Authors: Zeinab E. Attia, Ahmed M. Gadallah, Hesham A. Hefny
10.5120/15940-5156
PDF

Zeinab E. Attia, Ahmed M. Gadallah, Hesham A. Hefny . Semantic Information Retrieval Model: Fuzzy Ontology Approach. International Journal of Computer Applications. 91, 13 (April 2014), 9-14. DOI=10.5120/15940-5156

                        @article{ 10.5120/15940-5156,
                        author  = { Zeinab E. Attia,Ahmed M. Gadallah,Hesham A. Hefny },
                        title   = { Semantic Information Retrieval Model: Fuzzy Ontology Approach },
                        journal = { International Journal of Computer Applications },
                        year    = { 2014 },
                        volume  = { 91 },
                        number  = { 13 },
                        pages   = { 9-14 },
                        doi     = { 10.5120/15940-5156 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2014
                        %A Zeinab E. Attia
                        %A Ahmed M. Gadallah
                        %A Hesham A. Hefny
                        %T Semantic Information Retrieval Model: Fuzzy Ontology Approach%T 
                        %J International Journal of Computer Applications
                        %V 91
                        %N 13
                        %P 9-14
                        %R 10.5120/15940-5156
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

The paper proposes a multi-view information retrieval model. The model has the ability to deal with the multi-field topics problem using a predefined multi-field or multi-view fuzzy ontology. Respecting the natural relationship between concepts and terms, the model enhances the recall measure compared with previously proposed fuzzy ontology-based information retrieval models. It also proposes a ranking algorithm that ranks a set of relevant documents according to some criteria such as their relevance degree, confidence degree, and updating degree.

References
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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Information Retrieval Fuzzy ontology-based information retrieval fuzzy ontology

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