Textual Emotion Classification Using Deep Broad Learning
Author: Sancheng Peng
Publisher: Springer Nature
Published:
Total Pages: 167
ISBN-13: 3031677188
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Sentiment Analysis
Author: Bing Liu
Publisher: Cambridge University Press
Published: 2020-10-15
Total Pages: 451
ISBN-13: 1108787282
DOWNLOAD EBOOKSentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.
Web and Big Data
Author: Leong Hou U
Publisher: Springer Nature
Published: 2021-08-18
Total Pages: 515
ISBN-13: 3030858960
DOWNLOAD EBOOKThis two-volume set, LNCS 12858 and 12859, constitutes the thoroughly refereed proceedings of the 5th International Joint Conference, APWeb-WAIM 2021, held in Guangzhou, China, in August 2021. The 44 full papers presented together with 24 short papers, and 6 demonstration papers were carefully reviewed and selected from 184 submissions. The papers are organized around the following topics: Graph Mining; Data Mining; Data Management; Topic Model and Language Model Learning; Text Analysis; Text Classification; Machine Learning; Knowledge Graph; Emerging Data Processing Techniques; Information Extraction and Retrieval; Recommender System; Spatial and Spatio-Temporal Databases; and Demo.
Deep Learning-Based Approaches for Sentiment Analysis
Author: Basant Agarwal
Publisher: Springer Nature
Published: 2020-01-24
Total Pages: 326
ISBN-13: 9811512167
DOWNLOAD EBOOKThis 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. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field.
Emotions Across Languages and Cultures
Author: Anna Wierzbicka
Publisher: Cambridge University Press
Published: 1999-11-18
Total Pages: 366
ISBN-13: 9780521599719
DOWNLOAD EBOOKThis fascinating book explores the bodily expression of emotion in worldwide and culture-specific contexts.
Progress in Advanced Computing and Intelligent Engineering
Author: Chhabi Rani Panigrahi
Publisher: Springer Nature
Published: 2021-04-15
Total Pages: 883
ISBN-13: 9813342994
DOWNLOAD EBOOKThis book focuses on theory, practice and applications in the broad areas of advanced computing techniques and intelligent engineering. This book includes 74 scholarly articles which were accepted for presentation from 294 submissions in the 5th ICACIE during 25–27 June 2020 at Université des Mascareignes (UdM), Mauritius, in collaboration with Rama Devi Women’s University, Bhubaneswar, India, and S‘O’A Deemed to be University, Bhubaneswar, India. This book brings together academicians, industry persons, research scholars and students to share and disseminate their knowledge and scientific research work related to advanced computing and intelligent engineering. It helps to provide a platform to the young researchers to find the practical challenges encountered in these areas of research and the solutions adopted. The book helps to disseminate the knowledge about some innovative and active research directions in the field of advanced computing techniques and intelligent engineering, along with some current issues and applications of related topics.
Futuristic Trends in Networks and Computing Technologies
Author: Pradeep Kumar Singh
Publisher: Springer Nature
Published: 2020-04-21
Total Pages: 717
ISBN-13: 9811544514
DOWNLOAD EBOOKThis book constitutes the refereed proceedings of the Second International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2019, held in Chandigarh, India, in November 2019. The 49 revised full papers and 6 short papers presented were carefully reviewed and selected from 226 submissions. The prime aim of the conference is to invite researchers from different domains of network and communication technologies to a single platform to showcase their research ideas. The selected papers are organized in topical sections on network and computing technologies; wireless networks and Internet of Things (IoT); futuristic computing technologies; communication technologies, security and privacy.
The Oxford Handbook of Computational Linguistics
Author: Ruslan Mitkov
Publisher: Oxford University Press
Published: 2004
Total Pages: 808
ISBN-13: 019927634X
DOWNLOAD EBOOKThis handbook of computational linguistics, written for academics, graduate students and researchers, provides a state-of-the-art reference to one of the most active and productive fields in linguistics.
Practical Natural Language Processing
Author: Sowmya Vajjala
Publisher: O'Reilly Media
Published: 2020-06-17
Total Pages: 455
ISBN-13: 149205402X
DOWNLOAD EBOOKMany books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective
Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing
Author: Simon James Fong
Publisher: Springer Nature
Published: 2020-08-25
Total Pages: 228
ISBN-13: 981156695X
DOWNLOAD EBOOKThis book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases. The subject area of this book is within the realm of computer science, notably algorithms (meta-heuristic and, more particularly, bio-inspired algorithms). Although application domains of these new algorithms may be mentioned, the scope of this book is not on the application of algorithms to specific or general domains but to provide an update on recent research trends for bio-inspired algorithms within a specific application domain or emerging area. These areas include data streaming, fog computing, and phases of big data management. One of the reasons for writing this book is that the bio-inspired approach does not receive much attention but shows considerable promise and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase such as data mining or business intelligence as many books focus on); effective demonstration of the effectiveness of a selected algorithm within a chapter against comparative algorithms using the experimental method. Another novel approach is a brief overview and evaluation of traditional algorithms, both sequential and parallel, for use in data mining, in order to provide an overview of existing algorithms in use. This overview complements a further chapter on bio-inspired algorithms for data mining to enable readers to make a more suitable choice of algorithm for data mining within a particular context. In all chapters, references for further reading are provided, and in selected chapters, the author also include ideas for future research.
