Data Mining Approaches for Big Data and Sentiment Analysis in Social Media, Gupta Brij B., Perakovic Dragan, Abd El-Latif Ahmed A.
Автор: Sharaff Aakanksha, Sinha G. R., Bhatia Surbhi Название: New Opportunities for Sentiment Analysis and Information Processing ISBN: 1799880621 ISBN-13(EAN): 9781799880622 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 196810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Multinational organizations have begun to realize that sentiment mining plays an important role for decision making and market strategy. The revolutionary growth of digital marketing not only changes the market game, but also brings forth new opportunities for skilled professionals and expertise. Currently, the technologies are rapidly changing, and artificial intelligence (AI) and machine learning are contributing as game-changing technologies. These are not only trending but are also increasingly popular among data scientists and data analysts.
New Opportunities for Sentiment Analysis and Information Processing provides interdisciplinary research in information retrieval and sentiment analysis including studies on extracting sentiments from textual data, sentiment visualization-based dimensionality reduction for multiple features, and deep learning-based multi-domain sentiment extraction. The book also optimizes techniques used for sentiment identification and examines applications of sentiment analysis and emotion detection. Covering such topics as communication networks, natural language processing, and semantic analysis, this book is essential for data scientists, data analysts, IT specialists, scientists, researchers, academicians, and students.
Автор: Gupta Brij B., Perakovic Dragan, Abd El-Latif Ahmed A. Название: Data Mining Approaches for Big Data and Sentiment Analysis in Social Media ISBN: 1799884147 ISBN-13(EAN): 9781799884149 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 189420.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Social media sites are constantly evolving with huge amounts of scattered data or big data, which makes it difficult for researchers to trace the information flow. It is a daunting task to extract a useful piece of information from the vast unstructured big data; the disorganized structure of social media contains data in various forms such as text and videos as well as huge real-time data on which traditional analytical methods like statistical approaches fail miserably. Due to this, there is a need for efficient data mining techniques that can overcome the shortcomings of the traditional approaches.
Data Mining Approaches for Big Data and Sentiment Analysis in Social Media encourages researchers to explore the key concepts of data mining, such as how they can be utilized on online social media platforms, and provides advances on data mining for big data and sentiment analysis in online social media, as well as future research directions. Covering a range of concepts from machine learning methods to data mining for big data analytics, this book is ideal for graduate students, academicians, faculty members, scientists, researchers, data analysts, social media analysts, managers, and software developers who are seeking to learn and carry out research in the area of data mining for big data and sentiment.
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: 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: Arindam Chaudhuri Название: Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks ISBN: 9811374732 ISBN-13(EAN): 9789811374739 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to date, but most of the current methods focus on either only textual content, or only visual content. In contrast, the proposed sentiment analysis model can be applied to any social blog dataset, making the book highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis. The mathematical abstraction of the sentiment analysis model is presented in a very lucid manner. The complete sentiments are analysed by combining text and visual prediction results. The book’s novelty lies in its development of innovative hierarchical recurrent neural networks for analysing sentiments; stacking of multiple recurrent layers by controlling the signal flow from upper recurrent layers to lower layers through a global gating unit; evaluation of HGFRNNs with different types of recurrent units; and adaptive assignment of HGFRNN layers to different timescales. Considering the need to leverage large-scale social multimedia content for sentiment analysis, both state-of-the-art visual and textual sentiment analysis techniques are used for joint visual-textual sentiment analysis. The proposed method yields promising results from Twitter datasets that include both texts and images, which support the theoretical hypothesis.
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: Sharaff Aakanksha, Sinha G. R., Bhatia Surbhi Название: New Opportunities for Sentiment Analysis and Information Processing ISBN: 1799880613 ISBN-13(EAN): 9781799880615 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 260570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Multinational organizations have begun to realize that sentiment mining plays an important role for decision making and market strategy. The revolutionary growth of digital marketing not only changes the market game, but also brings forth new opportunities for skilled professionals and expertise. Currently, the technologies are rapidly changing, and artificial intelligence (AI) and machine learning are contributing as game-changing technologies. These are not only trending but are also increasingly popular among data scientists and data analysts.
New Opportunities for Sentiment Analysis and Information Processing provides interdisciplinary research in information retrieval and sentiment analysis including studies on extracting sentiments from textual data, sentiment visualization-based dimensionality reduction for multiple features, and deep learning-based multi-domain sentiment extraction. The book also optimizes techniques used for sentiment identification and examines applications of sentiment analysis and emotion detection. Covering such topics as communication networks, natural language processing, and semantic analysis, this book is essential for data scientists, data analysts, IT specialists, scientists, researchers, academicians, and students.
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: Anna Atefeh Farzindar, Diana Inkpen Название: Natural Language Processing for Social Media ISBN: 1681738139 ISBN-13(EAN): 9781681738130 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 95170.00 T Наличие на складе: Нет в наличии. Описание: In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms that extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. This book will discuss the challenges in analyzing social media texts in contrast with traditional documents.
Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts, and it shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, and business intelligence. The book further covers the existing evaluation metrics for NLP and social media applications and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks), the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC), or the Conference and Labs of the Evaluation Forum (CLEF).
In this third edition of the book, the authors added information about recent progress in NLP for social media applications, including more about the modern techniques provided by deep neural networks (DNNs) for modeling language and analyzing social media data.
Автор: Anna Atefeh Farzindar, Diana Inkpen Название: Natural Language Processing for Social Media ISBN: 1681738112 ISBN-13(EAN): 9781681738116 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 75770.00 T Наличие на складе: Нет в наличии. Описание: In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms that extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. This book will discuss the challenges in analyzing social media texts in contrast with traditional documents.
Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts, and it shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, and business intelligence. The book further covers the existing evaluation metrics for NLP and social media applications and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks), the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC), or the Conference and Labs of the Evaluation Forum (CLEF).
In this third edition of the book, the authors added information about recent progress in NLP for social media applications, including more about the modern techniques provided by deep neural networks (DNNs) for modeling language and analyzing social media data.
Автор: Shalin Hai-Jew Название: Social Media Data Extraction and Content Analysis ISBN: 1522506489 ISBN-13(EAN): 9781522506485 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 222690.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Explores various social networking platforms and the technologies being utilized to gather and analyse information being posted to these venues. Highlighting emergent research, analytical techniques, and best practices in data extraction in global electronic culture, this publication is an essential reference source for researchers, academics, and professionals.
Автор: Muhammad Sarfraz Название: Critical Approaches to Information Retrieval Research ISBN: 1799810216 ISBN-13(EAN): 9781799810216 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 174630.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Information retrieval (IR) is considered to be the science of searching for information from a variety of information sources related to texts, images, sounds, or multimedia. With the rise of the internet and digital databases, updated information retrieval methodologies are essential to ensure the continued facilitation and enhancement of information exchange.
Critical Approaches to Information Retrieval Research is a critical scholarly publication that provides multidisciplinary examinations of theoretical innovations and methods in information retrieval technologies including search and storage applications for data, text, image, sound, document, and video retrieval. Featuring a wide range of topics including data mining, machine learning, and ontology, this book is ideal for librarians, software engineers, data scientists, professionals, researchers, information engineers, scientists, practitioners, and academicians working in the fields of computer science, information technology, information and communication sciences, education, health, library, and more.
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