Advances in Social Networking-Based Learning: Machine Learning-Based User Modelling and Sentiment Analysis, Troussas Christos, Virvou Maria

Автор: Jacques Janssen; Christos H. Skiadas; Constantin Z
Название: Advances in Stochastic Modelling and Data Analysis
ISBN: 9048145740 ISBN-13(EAN): 9789048145744
Издательство: Springer
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Цена: 111760.00 T
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Описание: Audience: A wide readership drawn from theoretical and applied mathematicians, such as operations researchers, management scientists, statisticians, computer scientists, bankers, marketing managers, forecasters, and scientific societies such as EURO and TIMS.

Автор: Sudipto Chaki; Sujit Ghosal
Название: Modelling and Optimisation of Laser Assisted Oxygen (LASOX) Cutting: A Soft Computing Based Approach
ISBN: 3030049027 ISBN-13(EAN): 9783030049027
Издательство: Springer
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Цена: 51230.00 T
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Описание: This book presents the basics of the Laser Assisted Oxygen (LASOX) cutting process, its development, advantages and shortcomings, together with detailed information on the research work carried out to date regarding the modelling and optimization of the process. It introduces two integrated soft computing-based models consisting of Artificial Neural Networks (ANN-GA and ANN SA) for the modelling and optimization of LASOX cutting. It also includes an in-depth discussion on the basic working algorithms of soft computing tools such as Artificial Neural Networks, Genetic Algorithms, Simulated Annealing etc. The book not only provides an approach to optimizing LASOX by means of soft computing-based integrated models, but also illustrates the practical implementation of the proposed models.

Автор: Jim E. Greer; Gordon I. McCalla
Название: Student Modelling: The Key to Individualized Knowledge-Based Instruction
ISBN: 3540575103 ISBN-13(EAN): 9783540575108
Издательство: Springer
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Цена: 204040.00 T
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Описание: Student modelling gives an intelligent tutoring system the ability to individualize its interactions with the student. This volume provides an overview of student modelling.

Автор: Peсa-Ayala Alejandro
Название: Educational Networking: A Novel Discipline for Improved Learning Based on Social Networks
ISBN: 3030299759 ISBN-13(EAN): 9783030299750
Издательство: Springer
Цена: 93160.00 T
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Описание: PartI: Reviews.- Chapter1: Educational Networking: A Novel Discipline for Improved K-12 Learning Based on Social Networks.- Chapter2: Reviewing Mixed Methods Approaches Using Social Network Analysis for Learning and Education.- Chapter3: Educational Networking: A Glimpse at Emergent Field.- PartII: Conceptual.- Chapter4: The Platform Adoption Model (PAM): A theoretical framework to address barriers to educational networking.- PartIII: Projects.- Chapter5: Groups and Networks: Teachers' Educational Networking at B@UNAM.- Chapter6: Developing a learning network on YouTube: Analysis of student satisfaction with a learner-generated content activity.- PartIV: Approaches.- Chapter7: e-Assessments via Wiki and Blog Tools: Students' Perspective.- Chapter8: Lurkers vs. Posters: Investigation of the Participation Behaviors in Online Learning Communities.- Chapter9: Learning Spaces in Context-Aware Educational Networking Technologies in the digital age.- PartV: Study.- Chapter10: Mexican university ranking based on maximal clique.

Автор: Witold Pedrycz; Shyi-Ming Chen
Название: Sentiment Analysis and Ontology Engineering
ISBN: 3319303171 ISBN-13(EAN): 9783319303178
Издательство: Springer
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Цена: 139310.00 T
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Описание:

Fundamentals of Sentiment Analysis and Its Applications.- Fundamentals of Sentiment Analysis: Concepts and Methodology.- The Comprehension of Figurative Language: What is the Influence of Irony and Sarcasm on NLP Techniques?.- Probabilistic Approaches for Sentiment Analysis: Latent Dirichlet Allocation for Ontology Building and Sentiment Extraction.- Description Logic Class Expression Learning Applied to Sentiment Analysis.- Capturing Digest Emotions by Means of Fuzzy Linguistic Aggregation.- Hyperelastic-based Adaptive Dynamics Methodology in Knowledge Acquisition for Computational Intelligence on Ontology Engineering of Evolving Folksonomy Driven Environment.- Sentiment-Oriented Information Retrieval: Affective Analysis of Documents Based on the SenticNet Framework.- Interpretability of Computational Models for Sentiment Analysis.- Chinese Micro-blog Emotion Classification by Exploiting Linguistic Features and SVM^perf.- Social Media and News Sentiment Analysis for Advanced Investment Strategies.- Context Aware Customer Experience Management: A Development Framework Based on Ontologies and Computational Intelligence.- An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief.- Big Data Sentiment Analysis for Brand Monitoring in Social Media Streams by Cloud Computing.- Neuro-Fuzzy Sentiment Analysis for Customer Review Rating Prediction.- OntoLSA: An Integrated Text Mining System for Ontology Learning and Sentiment Analysis.- Knowledge-based Tweet Classification for Disease Sentiment Monitoring.

Автор: Ranjan Satapathy; Erik Cambria; Amir Hussain
Название: Sentiment Analysis in the Bio-Medical Domain
ISBN: 3319886096 ISBN-13(EAN): 9783319886091
Издательство: Springer
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Цена: 139750.00 T
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Автор: Liang Wang; Guoying Zhao; Li Cheng; Matti Pietik?i
Название: Machine Learning for Vision-Based Motion Analysis
ISBN: 1447126076 ISBN-13(EAN): 9781447126072
Издательство: Springer
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Цена: 153720.00 T
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Описание: Based on contributions to the International Workshop on Machine Learning for Vision-Based Motion Analysis, this volume highlights the latest algorithms and systems for robust and effective vision-based motion understanding.

Автор: Tsihrintzis George A., Jain Lakhmi C.
Название: Machine Learning Paradigms: Advances in Deep Learning-Based Technological Applications
ISBN: 3030497232 ISBN-13(EAN): 9783030497231
Издательство: Springer
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Цена: 139750.00 T
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Описание: Chapter 1: Introduction to Deep Learning-based Technological Applications.- Chapter 2: Vision to Language: Methods, Metrics and Datasets.- Chapter 3: Deep Learning Techniques for Geospatial Data Analysis.- Chapter 4: Deep Learning Approaches in Food Recognition.- Chapter 5: Deep Learning for Twitter Sentiment Analysis: the Effect of pre-trained Word Embedding.- Chapter 6: A Good Defense is a Strong DNN: Defending the IoT with Deep Neural Networks.- Chapter 7: Survey on Deep Learning Techniques for Medical Imaging Application Area.- Chapter 8: Deep Learning Methods in Electroencephalography.

Автор: Koen H. van Dam; Igor Nikolic; Zofia Lukszo
Название: Agent-Based Modelling of Socio-Technical Systems
ISBN: 9401782687 ISBN-13(EAN): 9789401782685
Издательство: Springer
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Цена: 111790.00 T
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Описание: Here is a practical introduction to agent-based modelling of socio-technical systems, based on methodology developed at TU Delft, which has been deployed in a number of case studies. Offers theory, methods and practical steps for creating real-world models.

Автор: Jorge Freire Sousa; Riccardo Rossi
Название: Computer-based Modelling and Optimization in Transportation
ISBN: 3319046292 ISBN-13(EAN): 9783319046297
Издательство: Springer
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Цена: 111790.00 T
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Описание: Decision Making and Decision Support (in Transportation).- Energy and Environmental Impacts (of Transportation).- (Urban) Network Design.- Optimization and Simulation (in Transportation).

Автор: Liu, Bing (university Of Illinois, Chicago)
Название: Sentiment analysis
ISBN: 1108486371 ISBN-13(EAN): 9781108486378
Издательство: Cambridge Academ
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Цена: 70740.00 T
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Описание: Sentiment analysis is the computational study of people`s opinions, emotions, and attitudes. This comprehensive introduction covers all core areas useful for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. The second edition includes new deep learning analysis methods.

Автор: Adamatti Diana Francisca
Название: Multi-Agent-Based Simulations Applied to Biological and Environmental Systems
ISBN: 1522517561 ISBN-13(EAN): 9781522517566
Издательство: Mare Nostrum (Eurospan)
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Цена: 199590.00 T
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Описание: The discovery and development of new computational methods have expanded the capabilities and uses of simulations. With agent-based models, the applications of computer simulations are significantly enhanced.Multi-Agent-Based Simulations Applied to Biological and Environmental Systems is a pivotal reference source for the latest research on the implementation of autonomous agents in computer simulation paradigms. Featuring extensive coverage on relevant applications, such as biodiversity conservation, pollution reduction, and environmental risk assessment, this publication is an ideal source for researchers, academics, engineers, practitioners, and professionals seeking material on various issues surrounding the use of agent-based simulations.