Описание: This book reports on an outstanding thesis thathas significantly advanced the state-of-the-art in the automated analysis andclassification of speech and music.
Автор: Basant Agarwal; Namita Mittal Название: Prominent Feature Extraction for Sentiment Analysis ISBN: 3319253417 ISBN-13(EAN): 9783319253411 Издательство: Springer Рейтинг: Цена: 18284.00 р. 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
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, Richi Nayak Название: Deep Learning-Based Approaches for Sentiment Analysis ISBN: 9811512159 ISBN-13(EAN): 9789811512155 Издательство: Springer Рейтинг: Цена: 22359.00 р. 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: Erik Cambria; Dipankar Das; Sivaji Bandyopadhyay; Название: A Practical Guide to Sentiment Analysis ISBN: 3319553925 ISBN-13(EAN): 9783319553924 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Sentiment analysis research has been started long back and recently it is one of the demanding research topics.
Автор: Erik Cambria; Dipankar Das; Sivaji Bandyopadhyay; Название: A Practical Guide to Sentiment Analysis ISBN: 3319856480 ISBN-13(EAN): 9783319856483 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Поставка под заказ.
Описание: Sentiment analysis research has been started long back and recently it is one of the demanding research topics.
Автор: Bo Pang Название: Opinion Mining and Sentiment Analysis ISBN: 1601981503 ISBN-13(EAN): 9781601981509 Издательство: Marston Book Services Рейтинг: Цена: 16335.00 р. 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: 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.
Автор: Soujanya Poria; Amir Hussain; Erik Cambria Название: Multimodal Sentiment Analysis ISBN: 3030069567 ISBN-13(EAN): 9783030069568 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Поставка под заказ.
Описание: This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer. This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion.The inclusion of key visualization and case studies will enable readers to understand better these approaches. Aimed at the Natural Language Processing, Affective Computing and Artificial Intelligence audiences, this comprehensive volume will appeal to a wide readership and will help readers to understand key details on multimodal sentiment analysis.
Автор: Shalin Hai-Jew Название: Social Media Data Extraction and Content Analysis ISBN: 1522506489 ISBN-13(EAN): 9781522506485 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 33403.00 р. 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: Nhung Do, J. Wenny Rahayu, Torab Torabi Название: Developments in Data Extraction, Management, and Analysis ISBN: 1466621486 ISBN-13(EAN): 9781466621480 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28413.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is an essential collection of research on the area of data mining and analytics. Presenting the most recent perspectives on data mining subjects and current issues, this book is useful for practitioners and academics alike.
Описание: Although there are a large number of grammar books that explain the form and meaning of the English modal auxiliaries, there are few resources that provide examples as to what modals could be used, and in which cases, when referring to successive clauses. Modal auxiliaries are among the most difficult structures to teach to students of English as a second or foreign language. Some combinations of modals are more commonly used than others, and pairs of modals are used to express a specific meaning. It is not well known, however, exactly which combinations of modals are more popular. Therefore, a method to extract modal auxiliaries in two consecutive clauses from the British National Corpus 2007 XML edition was developed and is discussed in this book.Pair modal frequencies were not well known since simple string match methods could not be used with embedded sentences, complex sentences and compound sentences. This problem was solved by defining rules of sentence structures to identify important clauses carrying the main ideas of sentences, extracting only the important clauses and calculating t-scores. A system was implemented by using computational linguistic techniques for extracting, parsing, and simplifying sentences for learners to study the use of modal auxiliaries. Which collocational expressions are more common? What is the appropriateness of the results? Learners and educators can make use of these results to gain a better understanding of modal auxiliaries, and to facilitate the process of teaching and learning English.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
