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Query Based Text Summarization by Zainab Zarah (10 results)

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  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

    • Softcover

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  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

    • Softcover

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    Taschenbuch. Condition: Neu. Query Based Text Summarization using Machine learning Approach | Learning Approaches | Zarah Zainab (u. a.) | Taschenbuch | 80 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139452828 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

    • Softcover

    Seller: Buchpark, Trebbin, GermanyBuchpark

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    Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Extraction of relevant information on a specific query from rapidly growing data is a concern for quiet time in order to scan and analyze data from all the related documents. Therefore, text summarization is paramount research area these days. It is about to find most relevant information from single or multi-documents. A reasonable amount of work is done in this area to overcome extensive searching and to reduce the time required. The knowledge-based and machine learning are the two methods for query-based text summarization where Machine learning approaches are mostly used for calculating probabilistic feature using Natural Language Processing (NLP) tools and techniques for both supervised and unsupervised learning. In the first part of this research work include to identify and analyze machine learning approaches for query-based text summarization for finding a useful summary for the users as specified by their need. In the second part, a comprehensive discussion is done to present the internal working mechanism of machine learning approaches for query-based text summarization.…

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

    • Softcover

    Seller: Buchpark, Trebbin, GermanyBuchpark

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    Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Extraction of relevant information on a specific query from rapidly growing data is a concern for quiet time in order to scan and analyze data from all the related documents. Therefore, text summarization is paramount research area these days. It is about to find most relevant information from single or multi-documents. A reasonable amount of work is done in this area to overcome extensive searching and to reduce the time required. The knowledge-based and machine learning are the two methods for query-based text summarization where Machine learning approaches are mostly used for calculating probabilistic feature using Natural Language Processing (NLP) tools and techniques for both supervised and unsupervised learning. In the first part of this research work include to identify and analyze machine learning approaches for query-based text summarization for finding a useful summary for the users as specified by their need. In the second part, a comprehensive discussion is done to present the internal working mechanism of machine learning approaches for query-based text summarization.…

  • Language: English

    Published by LAP LAMBERT Academic Publishing Feb 2019, 2019

    6139452821 / 9786139452828

    • Softcover
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    Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Extraction of relevant information on a specific query from rapidly growing data is a concern for quiet time in order to scan and analyze data from all the related documents. Therefore, text summarization is paramount research area these days. It is about to find most relevant information from single or multi-documents. A reasonable amount of work is done in this area to overcome extensive searching and to reduce the time required. The knowledge-based and machine learning are the two methods for query-based text summarization where Machine learning approaches are mostly used for calculating probabilistic feature using Natural Language Processing (NLP) tools and techniques for both supervised and unsupervised learning. In the first part of this research work include to identify and analyze machine learning approaches for query-based text summarization for finding a useful summary for the users as specified by their need. In the second part, a comprehensive discussion is done to present the internal working mechanism of machine learning approaches for query-based text summarization. 80 pp. Englisch.…

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

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    Seller: Majestic Books, Hounslow, United KingdomMajestic Books

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  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

    • Softcover
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    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Extraction of relevant information on a specific query from rapidly growing data is a concern for quiet time in order to scan and analyze data from all the related documents. Therefore, text summarization is paramount research area these days. It is about to find most relevant information from single or multi-documents. A reasonable amount of work is done in this area to overcome extensive searching and to reduce the time required. The knowledge-based and machine learning are the two methods for query-based text summarization where Machine learning approaches are mostly used for calculating probabilistic feature using Natural Language Processing (NLP) tools and techniques for both supervised and unsupervised learning. In the first part of this research work include to identify and analyze machine learning approaches for query-based text summarization for finding a useful summary for the users as specified by their need. In the second part, a comprehensive discussion is done to present the internal working mechanism of machine learning approaches for query-based text summarization.…

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

    • Softcover
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    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

    • Softcover
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    Seller: moluna, Greven, Germanymoluna

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Zainab ZarahZarah Zainab is Bachelor of Science in Computer Science. He graduated from the City University of Science and Information TechnologyPeshawar, Pakistan, Department of Computer Science. February, 2019.Extraction of rele. …

  • Language: English

    Published by LAP LAMBERT Academic Publishing Feb 2019, 2019

    6139452821 / 9786139452828

    • Softcover
    • Print on Demand

    Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Extraction of relevant information on a specific query from rapidly growing data is a concern for quiet time in order to scan and analyze data from all the related documents. Therefore, text summarization is paramount research area these days. It is about to find most relevant information from single or multi-documents. A reasonable amount of work is done in this area to overcome extensive searching and to reduce the time required. The knowledge-based and machine learning are the two methods for query-based text summarization where Machine learning approaches are mostly used for calculating probabilistic feature using Natural Language Processing (NLP) tools and techniques for both supervised and unsupervised learning. In the first part of this research work include to identify and analyze machine learning approaches for query-based text summarization for finding a useful summary for the users as specified by their need. In the second part, a comprehensive discussion is done to present the internal working mechanism of machine learning approaches for query-based text summarization.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch.…