Machine Learning Based Approaches (29 results)

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  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

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  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

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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 Novas Edições Acadêmicas, 2018

    6202188545 / 9786202188548

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    Taschenbuch. Condition: Neu. Emotions Detection in Music Lyrics | Using Machine Learning and Keyword-Based Approaches | Ricardo Malheiro | Taschenbuch | Englisch | 2018 | Novas Edições Acadêmicas | EAN 9786202188548 | 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

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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 CRC Press, 2026

    1032871903 / 9781032871905

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  • Language: English

    Published by CRC Press, 2026

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  • Language: English

    Published by CRC Press, 2026

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  • Language: English

    Published by CRC Press, 2026

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  • Language: English

    Published by Taylor and Francis Ltd, 2026

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  • Language: English

    Published by Taylor and Francis Ltd, 2026

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  • Language: English

    Published by CRC Press, 2026

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  • Language: English

    Published by CRC Press, 2026

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  • Language: English

    Published by Taylor & Francis Ltd, 2026

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  • Language: English

    Published by CRC Press, 2026

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  • Language: English

    Published by CRC Press, 2026

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  • Language: English

    Published by CRC Press, 2026

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    Condition: New. Anirban Mukherjee has a Bachelors in Civil Engineering (1994) from Jadavpur University, Kolkata and PhD from Indian Institute of Engineering, Science and Technology (IIEST), Shibpur, India. He has been a Professor in the Department of Information .

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    Hardcover. Condition: Brand New. 268 pages. 9.18x6.12x9.21 inches. In Stock.

  • Language: English

    Published by Wiley-Scrivener, 2021

    1119786096 / 9781119786092

    Series: Book 2 of 2 - Machine Vision Inspection Systems

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  • Language: English

    Published by Taylor & Francis Ltd (Sales) Jun 2026, 2026

    1032871903 / 9781032871905

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    Buch. Condition: Neu. Neuware - The use of intelligent technologies to enhance instruction and learning is introduced in pedagogy-based learning-teaching perspective. It covers digital library resources, AI-based tools, data analysis techniques, and NLP and NLU-powered smart assistants. Students will realize their improved efficacy through use of expandable AI systems improve educational efficiency, automate repetitive chores, and enable personalized learning. The course offers useful skills for implementing contemporary AI methods in educational institutions, classrooms, and online learning settings.This book provides concise summary of forthcoming Intelligent Tools and Techniques that are using AI-based Learning-Teaching systems to shape contemporary education. It describes how NLP and NLU applications enhance intelligent teaching assistants, showcases sophisticated library resources for promoting informal learning. The book delivers a succinct but thorough approach for implementing scalable, effective, intelligent solutions that improve learning environments across a variety of educational settings through focused insights into educational data analysis and frameworks for expandable AI.Teachers, researchers, and students who wish to apply intelligent technology in the classroom are the target audience for this book. It works well for developers making intelligent learning tools, librarians overseeing digital resources, and educators investigating AI-based approaches. The book provides clear instructions on using AI, data analysis, and intelligent systems to enhance teaching, learning, and educational resource management, which will be beneficial to academic institutions, policymakers, and EdTech experts.Key features: - Contains applications of machine learning in performance analysis of students, which is helpful in designing rubrics for accreditation. - Deals with comparative study about outcome-based education and conventional educational system through application of statistical techniques. - Analyses role of emotional intelligence in measuring holistic performance of students - Evaluates different pedagogical approaches like active, authenticate, flipped, blended learning using neural network approaches. - Proposes different mathematical models for implementation of OBE for technical Institutions.

  • Language: English

    Published by Wiley-Scrivener, 2021

    1119786096 / 9781119786092

    Series: Book 2 of 2 - Machine Vision Inspection Systems

    • Hardcover

    Seller: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, GermanyBUCHSERVICE / ANTIQUARIAT Lars Lutzer

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    Condition: gut. Machine Vision Inspection Systems: Volume 2: Machine Learning-Based Approaches In englischer Sprache. pages.

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    paperback. Condition: New. Paperback. Pub Date: 2021-09-01 Pages: 324 Language: Chinese Publisher: Economic Science Press Economic Policy Evaluation and Forecast: A Method Based on Causal Inference and Machine Learning uses the causal inference and prediction in the evaluation and prediction of economic policy effects The machine learning method is the main research object. and the specific content can be divided into two main parts. The first part is the identification strategy of policy project effect evaluation. the.

  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

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  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

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  • Language: English

    Published by LAP LAMBERT Academic Publishing, 2019

    6139452821 / 9786139452828

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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 Taylor & Francis Ltd, London, 2026

    1032871903 / 9781032871905

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    Hardcover. Condition: new. Hardcover. The use of intelligent technologies to enhance instruction and learning is introduced in pedagogy-based learning-teaching perspective. It covers digital library resources, AI-based tools, data analysis techniques, and NLP and NLU-powered smart assistants. Students will realize their improved efficacy through use of expandable AI systems improve educational efficiency, automate repetitive chores, and enable personalized learning. The course offers useful skills for implementing contemporary AI methods in educational institutions, classrooms, and online learning settings.This book provides concise summary of forthcoming Intelligent Tools and Techniques that are using AI-based Learning-Teaching systems to shape contemporary education. It describes how NLP and NLU applications enhance intelligent teaching assistants, showcases sophisticated library resources for promoting informal learning. The book delivers a succinct but thorough approach for implementing scalable, effective, intelligent solutions that improve learning environments across a variety of educational settings through focused insights into educational data analysis and frameworks for expandable AI.Teachers, researchers, and students who wish to apply intelligent technology in the classroom are the target audience for this book. It works well for developers making intelligent learning tools, librarians overseeing digital resources, and educators investigating AI-based approaches. The book provides clear instructions on using AI, data analysis, and intelligent systems to enhance teaching, learning, and educational resource management, which will be beneficial to academic institutions, policymakers, and EdTech experts.Key features:Contains applications of machine learning in performance analysis of students, which is helpful in designing rubrics for accreditation.Deals with comparative study about outcome-based education and conventional educational system through application of statistical techniques.Analyses role of emotional intelligence in measuring holistic performance of studentsEvaluates different pedagogical approaches like active, authenticate, flipped, blended learning using neural network approaches.Proposes different mathematical models for implementation of OBE for technical Institutions. This book offers cutting-edge Intelligent Tools and Techniques that use AI-based Teaching-Learning approaches to enhance education. It describes methods of self-learning with aid of updated library resources that encourage informal learning. The book provides a useful manual for utilizing smart technology to improve learning experiences. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Language: English

    Published by Novas Edições Acadêmicas, 2018

    6202188545 / 9786202188548

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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 - Search of music through emotions is one of the main criteria utilized by users on Internet. Real-world music databases from sites like AllMusic or Last.fm grow larger and larger on a daily basis, which requires a tremendous amount of manual work for keeping them updated. As manual annotation with emotion tags is an expensive time-consuming task, we need automatic Music Emotion Recognition systems (MER). This book is focused on the task of automatic detection of emotions in music lyrics and in the importance of the different music dimensions (e.g., audio, lyrics) for the task of detection of emotions in music. In this book, different emotion detection approaches are analyzed and a new system is proposed. Topics such as relation between music features and emotions and music emotion variation detection are covered, as well as, identification of the most important music features to each emotion. This analysis contributes to unify the current efforts in this area. It should be particularly useful to researchers working in MER in general and in detection of emotions in music lyrics or general text in particular and as support to (under)graduate courses related to these topics.

  • Language: English

    Published by Taylor & Francis Ltd, London, 2026

    1032871903 / 9781032871905

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    Hardcover. Condition: new. Hardcover. The use of intelligent technologies to enhance instruction and learning is introduced in pedagogy-based learning-teaching perspective. It covers digital library resources, AI-based tools, data analysis techniques, and NLP and NLU-powered smart assistants. Students will realize their improved efficacy through use of expandable AI systems improve educational efficiency, automate repetitive chores, and enable personalized learning. The course offers useful skills for implementing contemporary AI methods in educational institutions, classrooms, and online learning settings.This book provides concise summary of forthcoming Intelligent Tools and Techniques that are using AI-based Learning-Teaching systems to shape contemporary education. It describes how NLP and NLU applications enhance intelligent teaching assistants, showcases sophisticated library resources for promoting informal learning. The book delivers a succinct but thorough approach for implementing scalable, effective, intelligent solutions that improve learning environments across a variety of educational settings through focused insights into educational data analysis and frameworks for expandable AI.Teachers, researchers, and students who wish to apply intelligent technology in the classroom are the target audience for this book. It works well for developers making intelligent learning tools, librarians overseeing digital resources, and educators investigating AI-based approaches. The book provides clear instructions on using AI, data analysis, and intelligent systems to enhance teaching, learning, and educational resource management, which will be beneficial to academic institutions, policymakers, and EdTech experts.Key features:Contains applications of machine learning in performance analysis of students, which is helpful in designing rubrics for accreditation.Deals with comparative study about outcome-based education and conventional educational system through application of statistical techniques.Analyses role of emotional intelligence in measuring holistic performance of studentsEvaluates different pedagogical approaches like active, authenticate, flipped, blended learning using neural network approaches.Proposes different mathematical models for implementation of OBE for technical Institutions. This book offers cutting-edge Intelligent Tools and Techniques that use AI-based Teaching-Learning approaches to enhance education. It describes methods of self-learning with aid of updated library resources that encourage informal learning. The book provides a useful manual for utilizing smart technology to improve learning experiences. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

  • Language: English

    Published by Taylor & Francis Ltd, London, 2026

    1032871903 / 9781032871905

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    Hardcover. Condition: new. Hardcover. The use of intelligent technologies to enhance instruction and learning is introduced in pedagogy-based learning-teaching perspective. It covers digital library resources, AI-based tools, data analysis techniques, and NLP and NLU-powered smart assistants. Students will realize their improved efficacy through use of expandable AI systems improve educational efficiency, automate repetitive chores, and enable personalized learning. The course offers useful skills for implementing contemporary AI methods in educational institutions, classrooms, and online learning settings.This book provides concise summary of forthcoming Intelligent Tools and Techniques that are using AI-based Learning-Teaching systems to shape contemporary education. It describes how NLP and NLU applications enhance intelligent teaching assistants, showcases sophisticated library resources for promoting informal learning. The book delivers a succinct but thorough approach for implementing scalable, effective, intelligent solutions that improve learning environments across a variety of educational settings through focused insights into educational data analysis and frameworks for expandable AI.Teachers, researchers, and students who wish to apply intelligent technology in the classroom are the target audience for this book. It works well for developers making intelligent learning tools, librarians overseeing digital resources, and educators investigating AI-based approaches. The book provides clear instructions on using AI, data analysis, and intelligent systems to enhance teaching, learning, and educational resource management, which will be beneficial to academic institutions, policymakers, and EdTech experts.Key features:Contains applications of machine learning in performance analysis of students, which is helpful in designing rubrics for accreditation.Deals with comparative study about outcome-based education and conventional educational system through application of statistical techniques.Analyses role of emotional intelligence in measuring holistic performance of studentsEvaluates different pedagogical approaches like active, authenticate, flipped, blended learning using neural network approaches.Proposes different mathematical models for implementation of OBE for technical Institutions. This book offers cutting-edge Intelligent Tools and Techniques that use AI-based Teaching-Learning approaches to enhance education. It describes methods of self-learning with aid of updated library resources that encourage informal learning. The book provides a useful manual for utilizing smart technology to improve learning experiences. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.