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A Proposed approach for fuzzy ontology-based information retrieval / Zeinab Ezz Elarab Attia ; Supervised Hesham A. Hefny , Ahmed M. Gadallah

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Zeinab Ezz Elarab Attia , 2014Description: 131 P. : charts ; 30cmOther title:
  • أسلوب مقترح معتمد على الفازى أونطولوجى لأسترجاع المعلومات [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and information sciences Summary: Current Information Retrieval (IR) models su{uFB00}er 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 su{uFB00}er from their unability to deal with any multi-{uFB01}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-{uFB01}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-{uFB01}eld topics using the proposed multi-{uFB01}eld term weighting algorithm, and handle user linguistic queries using the pro- posed linguistic-based multi-view fuzzy ontology tool
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.M.Sc.2014.Ze.P (Browse shelf(Opens below)) Not for loan 01010110064963000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.M.Sc.2014.Ze.P (Browse shelf(Opens below)) 64963.CD Not for loan 01020110064963000

Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and information sciences

Current Information Retrieval (IR) models su{uFB00}er 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 su{uFB00}er from their unability to deal with any multi-{uFB01}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-{uFB01}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-{uFB01}eld topics using the proposed multi-{uFB01}eld term weighting algorithm, and handle user linguistic queries using the pro- posed linguistic-based multi-view fuzzy ontology tool

Issued also as CD

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