Advances in Social Networking-Based Learning: Machine Learning-Based User Modelling and Sentiment Analysis, Troussas Christos, Virvou Maria
Автор: Basant Agarwal, Richi Nayak Название: Deep Learning-Based Approaches for Sentiment Analysis ISBN: 9811512159 ISBN-13(EAN): 9789811512155 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years.
Автор: Basant Agarwal; Namita Mittal Название: Prominent Feature Extraction for Sentiment Analysis ISBN: 3319253417 ISBN-13(EAN): 9783319253411 Издательство: Springer Рейтинг: Цена: 121890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
1 Introduction
2 Literature Survey
3 Machine Learning Approach for Sentiment Analysis
4 Semantic Parsing using Dependency Rules
5 Sentiment Analysis using ConceptNet Ontology and Context
Information
6 Semantic Orientation based Approach for Sentiment Analysis
7 Conclusions and FutureWork
References
Glossary Index
Автор: Liu, Bing (university Of Illinois, Chicago) Название: Sentiment analysis ISBN: 1108486371 ISBN-13(EAN): 9781108486378 Издательство: Cambridge Academ Рейтинг: Цена: 70740.00 T 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.
Автор: Agarwal Basant, Mittal Namita Название: Prominent Feature Extraction for Sentiment Analysis ISBN: 3319797751 ISBN-13(EAN): 9783319797755 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
1 Introduction
2 Literature Survey
3 Machine Learning Approach for Sentiment Analysis
4 Semantic Parsing using Dependency Rules
5 Sentiment Analysis using ConceptNet Ontology and Context
Information
6 Semantic Orientation based Approach for Sentiment Analysis
7 Conclusions and FutureWork
References
Glossary Index
Автор: Troussas Christos, Virvou Maria Название: Advances in Social Networking-Based Learning: Machine Learning-Based User Modelling and Sentiment Analysis ISBN: 3030391299 ISBN-13(EAN): 9783030391294 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book discusses three important, hot research issues: social networking-based learning, machine learning-based user modeling and sentiment analysis.
Автор: Agarwal Basant, Nayak Richi, Mittal Namita Название: Deep Learning-Based Approaches for Sentiment Analysis ISBN: 9811512183 ISBN-13(EAN): 9789811512186 Издательство: Springer Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years.
Автор: Bing Liu Название: Sentiment Analysis and Opinion Mining ISBN: 1608458849 ISBN-13(EAN): 9781608458844 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 41580.00 T Наличие на складе: Невозможна поставка. Описание: Sentiment analysis and opinion mining is the field of study that analyses people`s opinions, sentiments, evaluations, attitudes, and emotions from written language. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references.
Автор: Ranjan Satapathy; Erik Cambria; Amir Hussain Название: Sentiment Analysis in the Bio-Medical Domain ISBN: 3319886096 ISBN-13(EAN): 9783319886091 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Поставка под заказ.
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: Pozzi, Federico Название: Sentiment Analysis in Social Networks ISBN: 0128044128 ISBN-13(EAN): 9780128044124 Издательство: Elsevier Science Рейтинг: Цена: 49390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking.
Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature.
Further, this volume:
Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies
Provides insights into opinion spamming, reasoning, and social network analysis
Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences
Serves as a one-stop reference for the state-of-the-art in social media analytics
Автор: Bo Pang Название: Opinion Mining and Sentiment Analysis ISBN: 1601981503 ISBN-13(EAN): 9781601981509 Издательство: Marston Book Services Рейтинг: Цена: 108900.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.
Автор: Witold Pedrycz; Shyi-Ming Chen Название: Sentiment Analysis and Ontology Engineering ISBN: 3319303171 ISBN-13(EAN): 9783319303178 Издательство: Springer Рейтинг: Цена: 139310.00 T 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.
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