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Enhanced clustering for textual case-based reasoning / Ehab Mohamed Elsayed Terra ; Supervised Mahmoud A. Mahmoud , Ammar Mohammed , Hesham A. Hefny

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ehab Mohamed Elsayed Terra , 2020Description: 109 P. : charts ; 30cmOther title:
  • التجمع المحسن للاستدلال المبنى على حالات نصية [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Graduate Studies for Statistical Research - Department of Computer and Information Science Summary: As a result of the rapid development in the means of communication and storage, the sheer amount of textual data that becomes larger every day.The main objective of the Textual Case-Based Reasoning (TCBR) is to benefit from the knowledge inside these text data to introduce solutions for the future problems. For this reason, TCBR sys- tems must intelligently detect the latent knowledge in the data and provide successful solutions to enormous requests from large number of users in a timely manner.That is making TCBR a challenging problem for several reasons, one of which because a single case may consists of different topics and complex linguistic terms, and the other is related to the efficiency and accuracy of the used Information Retrieval (IR) process itself. Many efforts have been made to enhance the retrieval process in TCBR using clus- tering and feature selection methods. SOPHIA (SOPHisticated Information Analysis) approach is one of the most successful efforts which is characterized by its ability to work without the domain of knowledge or language dependency. SOPHIA is based on the conditional probability, which facilitates an advanced Knowledge Discovery (KD) framework for case-based retrieval
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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.2020.Eh.E (Browse shelf(Opens below)) Not for loan 01010110081807000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.M.Sc.2020.Eh.E (Browse shelf(Opens below)) 81807.CD Not for loan 01020110081807000

Thesis (M.Sc.) - Cairo University - Graduate Studies for Statistical Research - Department of Computer and Information Science

As a result of the rapid development in the means of communication and storage, the sheer amount of textual data that becomes larger every day.The main objective of the Textual Case-Based Reasoning (TCBR) is to benefit from the knowledge inside these text data to introduce solutions for the future problems. For this reason, TCBR sys- tems must intelligently detect the latent knowledge in the data and provide successful solutions to enormous requests from large number of users in a timely manner.That is making TCBR a challenging problem for several reasons, one of which because a single case may consists of different topics and complex linguistic terms, and the other is related to the efficiency and accuracy of the used Information Retrieval (IR) process itself. Many efforts have been made to enhance the retrieval process in TCBR using clus- tering and feature selection methods. SOPHIA (SOPHisticated Information Analysis) approach is one of the most successful efforts which is characterized by its ability to work without the domain of knowledge or language dependency. SOPHIA is based on the conditional probability, which facilitates an advanced Knowledge Discovery (KD) framework for case-based retrieval

Issued also as CD

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