Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139452821 ISBN 13: 9786139452828
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 63,42
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139452821 ISBN 13: 9786139452828
Librería: preigu, Osnabrück, Alemania
EUR 36,25
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: 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.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139452821 ISBN 13: 9786139452828
Librería: Buchpark, Trebbin, Alemania
EUR 18,60
Cantidad disponible: 1 disponibles
Añadir al carritoCondición: 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.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139452821 ISBN 13: 9786139452828
Librería: Buchpark, Trebbin, Alemania
EUR 19,19
Cantidad disponible: 1 disponibles
Añadir al carritoCondición: 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.
Idioma: Inglés
Publicado por Novas Edições Acadêmicas, 2018
ISBN 10: 6202188545 ISBN 13: 9786202188548
Librería: preigu, Osnabrück, Alemania
EUR 59,40
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: 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.
Librería: Buchmarie, Darmstadt, Alemania
EUR 191,59
Cantidad disponible: 1 disponibles
Añadir al carritoCondición: Good.
ISBN 10: 7521829239 ISBN 13: 9787521829235
Librería: liu xing, Nanjing, JS, China
EUR 91,15
Cantidad disponible: 3 disponibles
Añadir al carritopaperback. Condición: 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.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139452821 ISBN 13: 9786139452828
Librería: Majestic Books, Hounslow, Reino Unido
EUR 59,22
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. Print on Demand.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139452821 ISBN 13: 9786139452828
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 64,09
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139452821 ISBN 13: 9786139452828
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 40,89
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: 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.
Idioma: Inglés
Publicado por Novas Edições Acadêmicas, 2018
ISBN 10: 6202188545 ISBN 13: 9786202188548
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 70,74
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: 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.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2026
ISBN 10: 1032871903 ISBN 13: 9781032871905
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 173,94
Cantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: 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.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2026
ISBN 10: 1032871903 ISBN 13: 9781032871905
Librería: CitiRetail, Stevenage, Reino Unido
EUR 175,07
Cantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: 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.