A Proposed approach for fuzzy ontology-based information retrieval /
Zeinab Ezz Elarab Attia
A Proposed approach for fuzzy ontology-based information retrieval / أسلوب مقترح معتمد على الفازى أونطولوجى لأسترجاع المعلومات Zeinab Ezz Elarab Attia ; Supervised Hesham A. Hefny , Ahmed M. Gadallah - Cairo : Zeinab Ezz Elarab Attia , 2014 - 131 P. : charts ; 30cm
Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and information sciences
Current Information Retrieval (IR) models suer from many retrieval prob- lems. Some of them are low in the recall measure, low in the percision mea- sure, and inaccuracy in ranking the resulted documents. Also they suer from their unability to deal with any multi-eld topics and unability to handle user linguistic-based queries. To Consider these problems, the thesis proposes a linguistic-based fuzzy in- formation retrieval model, a linguistic-based Multi-view Fuzzy Ontology tool, and a multi-eld term weighting algorithm. The proposed linguistic-based fuzzy information retrieval model aims to enhance the recall measure, enhancce the precision measure, and rank the resulted documents acccurately. Also it has the ability to deal with the multi-eld topics using the proposed multi-eld term weighting algorithm, and handle user linguistic queries using the pro- posed linguistic-based multi-view fuzzy ontology tool
Computer and information Fuzzy ontology Information retrieval
A Proposed approach for fuzzy ontology-based information retrieval / أسلوب مقترح معتمد على الفازى أونطولوجى لأسترجاع المعلومات Zeinab Ezz Elarab Attia ; Supervised Hesham A. Hefny , Ahmed M. Gadallah - Cairo : Zeinab Ezz Elarab Attia , 2014 - 131 P. : charts ; 30cm
Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and information sciences
Current Information Retrieval (IR) models suer from many retrieval prob- lems. Some of them are low in the recall measure, low in the percision mea- sure, and inaccuracy in ranking the resulted documents. Also they suer from their unability to deal with any multi-eld topics and unability to handle user linguistic-based queries. To Consider these problems, the thesis proposes a linguistic-based fuzzy in- formation retrieval model, a linguistic-based Multi-view Fuzzy Ontology tool, and a multi-eld term weighting algorithm. The proposed linguistic-based fuzzy information retrieval model aims to enhance the recall measure, enhancce the precision measure, and rank the resulted documents acccurately. Also it has the ability to deal with the multi-eld topics using the proposed multi-eld term weighting algorithm, and handle user linguistic queries using the pro- posed linguistic-based multi-view fuzzy ontology tool
Computer and information Fuzzy ontology Information retrieval