Advances in Social Networking-Based Learning: Machine Learning-Based User Modelling and Sentiment Analysis, Troussas Christos, Virvou Maria
Автор: Witold Pedrycz; Shyi-Ming Chen Название: Sentiment Analysis and Ontology Engineering ISBN: 3319303171 ISBN-13(EAN): 9783319303178 Издательство: Springer Рейтинг: Цена: 18237.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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 SVMperf.- 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.
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 SVMperf.- 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: Liu, Bing (university Of Illinois, Chicago) Название: Sentiment analysis ISBN: 1108486371 ISBN-13(EAN): 9781108486378 Издательство: Cambridge Academ Рейтинг: Цена: 10611.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Описание: This book demonstrates how to apply modern approaches to complex system control in practical applications involving knowledge-based systems. Moreover, specialised forms of knowledge-based systems (like e-learning, social network, and production systems) are introduced with a new formal approach to knowledge system modelling.
Автор: Jacques Janssen; Christos H. Skiadas; Constantin Z Название: Advances in Stochastic Modelling and Data Analysis ISBN: 9048145740 ISBN-13(EAN): 9789048145744 Издательство: Springer Рейтинг: Цена: 14630.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Baochang Zhang Название: Machine Learning and Visual Perception ISBN: 3110595532 ISBN-13(EAN): 9783110595536 Издательство: Walter de Gruyter Цена: 9288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Machine Learning and Visual Perception provides an up-to-date overview on the topic, including the PAC model, decision tree, Bayesian learning, support vector machines, AdaBoost, compressive sensing and so on.Both classic and novel algorithms are introduced in classifier design, face recognition, deep learning, time series recognition, image classification, and object detection.
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 Рейтинг: Цена: 20123.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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: Tsvi Kuflik; Shlomo Berkovsky; Francesca Carmagnol Название: Advances in Ubiquitous User Modelling ISBN: 3642050387 ISBN-13(EAN): 9783642050381 Издательство: Springer Рейтинг: Цена: 8537.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Ubiquitous user modeling differs from generic user modeling by three additional concepts: ongoing modeling, ongoing sharing, and ongoing exploitation. Systems that share their user models will improve the coverage, the level of detail, and the reliability of the integrated user models and thus allow better functions of adaptation.
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.
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.
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