Advanced Applications Of Nlp And Deep Learning In Social Media Data
DOWNLOAD
Download Advanced Applications Of Nlp And Deep Learning In Social Media Data PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Advanced Applications Of Nlp And Deep Learning In Social Media Data book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Advanced Applications Of Nlp And Deep Learning In Social Media Data
DOWNLOAD
Author : Abd El-Latif, Ahmed A.
language : en
Publisher: IGI Global
Release Date : 2023-06-05
Advanced Applications Of Nlp And Deep Learning In Social Media Data written by Abd El-Latif, Ahmed A. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-05 with Computers categories.
Social media platforms are one of the main generators of textual data where people around the world share their daily life experiences and information with online society. The social, personal, and professional lives of people on these social networking sites generate not only a huge amount of data but also open doors for researchers and academicians with numerous research opportunities. This ample amount of data needs advanced machine learning, deep learning, and intelligent tools and techniques to receive, process, and interpret the information to resolve real-life challenges and improve the online social lives of people. Advanced Applications of NLP and Deep Learning in Social Media Data bridges the gap between natural language processing (NLP), advanced machine learning, deep learning, and online social media. It hopes to build a better and safer social media space by making human language available on different social media platforms intelligible for machines with the blessings of AI. Covering topics such as machine learning-based prediction, emotion recognition, and high-dimensional text clustering, this premier reference source is an essential resource for OSN service providers, psychiatrists, psychologists, clinicians, sociologists, students and educators of higher education, librarians, researchers, and academicians.
Natural Language Processing For Social Media
DOWNLOAD
Author : Atefeh Farzindar
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2017-12-15
Natural Language Processing For Social Media written by Atefeh Farzindar and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-15 with Computers categories.
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 which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We 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 (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, healthcare, business intelligence, industry, marketing, and security and defence. We review 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) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, virtual reality, and social networking. In this second edition, we have added information about recent progress in the tasks and applications presented in the first edition. We discuss new methods and their results. The number of research projects and publications that use social media data is constantly increasing due to continuously growing amounts of social media data and the need to automatically process them. We have added 85 new references to the more than 300 references from the first edition. Besides updating each section, we have added a new application (digital marketing) to the section on media monitoring and we have augmented the section on healthcare applications with an extended discussion of recent research on detecting signs of mental illness from social media.
Deep Learning For Nlp And Speech Recognition
DOWNLOAD
Author : Uday Kamath
language : en
Publisher: Springer
Release Date : 2019-06-10
Deep Learning For Nlp And Speech Recognition written by Uday Kamath and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-10 with Computers categories.
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Deep Learning For Natural Language Processing
DOWNLOAD
Author : Palash Goyal
language : en
Publisher: Apress
Release Date : 2018-06-26
Deep Learning For Natural Language Processing written by Palash Goyal and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-26 with Computers categories.
Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You’ll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with practical examples. The first three chapters of the book cover the basics of NLP, starting with word-vector representation before moving onto advanced algorithms. The final chapters focus entirely on implementation, and deal with sophisticated architectures such as RNN, LSTM, and Seq2seq, using Python tools: TensorFlow, and Keras. Deep Learning for Natural Language Processing follows a progressive approach and combines all the knowledge you have gained to build a question-answer chatbot system. This book is a good starting point for people who want to get started in deep learning for NLP. All the code presented in the book will be available in the form of IPython notebooks and scripts, which allow you to try out the examples and extend them in interesting ways. What You Will Learn Gain the fundamentals of deep learning and its mathematical prerequisites Discover deep learning frameworks in Python Develop a chatbot Implement a research paper on sentiment classification Who This Book Is For Software developers who are curious to try out deep learning with NLP.
Exploring Psychology Social Innovation And Advanced Applications Of Machine Learning
DOWNLOAD
Author : Raygoza-L., Maria E.
language : en
Publisher: IGI Global
Release Date : 2025-03-06
Exploring Psychology Social Innovation And Advanced Applications Of Machine Learning written by Raygoza-L., Maria E. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-06 with Computers categories.
Machine learning (ML algorithms can be used to better understand human behavior in its various developmental stages and to assist in addressing psychological issues. Additionally, in the realm of mental health and well-being, algorithms can assist with early detection of disorders and customization of treatments as well as personalize recommendations and suggestions based on user behavior. By focusing on user experience and usability, ML may be used to address challenges faced by private enterprises and social issues. Exploring Psychology, Social Innovation and Advanced Applications of Machine Learning explores the relationships between human psychology and machine learning technology, enabling researchers to delve into areas such as user interface design, ethics in artificial intelligence, and the social impact of algorithms. Furthermore, it promotes interdisciplinary collaboration by bringing together perspectives from different fields, which could stimulate new research and innovative approaches in the field of machine learning. Covering topics such as industrial processes, digital therapy, and machine vision, this book is an excellent resource for psychologists, computer scientists, engineers, healthcare practitioners, educators, business leaders, policymakers, professionals, researchers, scholars, academicians, and more.
Basic Knowledge On Fintech
DOWNLOAD
Author : TABF Editorial Board
language : en
Publisher: Hyweb Technology Co. Ltd.
Release Date : 2020-04-01
Basic Knowledge On Fintech written by TABF Editorial Board and has been published by Hyweb Technology Co. Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-01 with Business & Economics categories.
As the field of FinTech continues its progress, financial institutions must not only enhance their digitization, but also make serious efforts to understand the resulting new opportunities it creates. In line with these developments, TABF has published the book Basic knowledge on FinTech, which was designed by us as a reference for the FinTech Knowledge Test. Co-authored by TABF staff and other experts, it features balanced and credible analysis, avoiding trivia and overly complex concepts while emphasizing readability. The content structure is based on the World Economic Forum (WEF)'s roadmap for FinTech development, adding in TABF's research findings plus other domestic and international trends and practices. Not only is Basic knowledge on FinTech suitable for financial proficiency testing, but it can also be used as a textbook in university courses, supplementing theoretical knowledge with up-to-date practical knowledge in this rapidly changing field.
Data Science Concepts And Techniques With Applications
DOWNLOAD
Author : Usman Qamar
language : en
Publisher: Springer Nature
Release Date : 2023-04-02
Data Science Concepts And Techniques With Applications written by Usman Qamar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-02 with Computers categories.
This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared to the first edition, is devoted to various techniques and tools applied in data science. Its chapters 4 to 10 detail data pre-processing, classification, clustering, text mining, deep learning, frequent pattern mining, and regression analysis. Eventually, the third part (chapters 11 and 12) present a brief introduction to Python and R, the two main data science programming languages, and shows in a completely new chapter practical data science in the WEKA (Waikato Environment for Knowledge Analysis), an open-source tool for performing different machine learning and data mining tasks. An appendix explaining the basic mathematical concepts of data science completes the book. This textbook is suitable for advanced undergraduate and graduate students as well as for industrial practitioners who carry out research in data science. They both will not only benefit from the comprehensive presentation of important topics, but also from the many application examples and the comprehensive list of further readings, which point to additional publications providing more in-depth research results or provide sources for a more detailed description of related topics. "This book delivers a systematic, carefully thoughtful material on Data Science." from the Foreword by Witold Pedrycz, U Alberta, Canada.
Big Data Analytics Course
DOWNLOAD
Author : Brian Smith
language : en
Publisher: THE PUBLISHER
Release Date : 2024-03-11
Big Data Analytics Course written by Brian Smith and has been published by THE PUBLISHER this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-11 with Computers categories.
In "The Big Data Analytics Course," readers are introduced to the world of big data and its significance in today's digital age. The book covers a wide range of topics, starting with an understanding of big data and its challenges. It then delves into data collection methods and storage technologies, emphasizing data quality and governance. The next section focuses on data processing and analysis, including techniques for preprocessing, analysis, and visualization. Readers are also introduced to popular big data technologies like Hadoop, Spark, and NoSQL databases. The book then explores the application of machine learning in big data, covering both supervised and unsupervised learning. Real-world applications of big data analytics are discussed, including its use in healthcare, finance, and e-commerce. The book also addresses data security and privacy concerns, emphasizing the importance of ethical use and considerations like bias, transparency, and accountability. Other topics covered include data mining and predictive analytics, scalable computing, data governance and management, business intelligence and decision support, IoT and big data, big data in social media, and advanced topics like text analytics, graph analytics, and deep learning for big data. Overall, "The Big Data Analytics Course" provides a comprehensive guide for understanding and utilizing big data analytics in various industries, emphasizing the importance of data-driven decision making and responsible use of data.
Artificial Intelligence And Society
DOWNLOAD
Author : Dr. R. B. Konda, Dr. Mahesh M. Ganwar, Prof. Kaveri Kori, Dr. Hanmanthappa Sedamkar, Dr. Manikamma S., Dr. Saibanna. & Dr. Mitradevi Halimani
language : en
Publisher: Laxmi Book Publication
Release Date : 2024-11-08
Artificial Intelligence And Society written by Dr. R. B. Konda, Dr. Mahesh M. Ganwar, Prof. Kaveri Kori, Dr. Hanmanthappa Sedamkar, Dr. Manikamma S., Dr. Saibanna. & Dr. Mitradevi Halimani and has been published by Laxmi Book Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-08 with Art categories.
The integration of AI-powered e-gamified modules in education has significantly impacted students' scientific attitudes and academic achievement in science. This study investigates how AI-driven gamification enhances engagement, critical thinking, and problem-solving skills, leading to improved academic performance. AI enables personalized learning experiences by adapting to individual student needs, thus fostering a more interactive and learner-centered approach. E-gamified modules provide immediate feedback, motivating students to correct errors and reinforce learning. The main aim of the study is to find out whether there is any significant difference between pre-test & post-test mean scores of secondary school students taught with and without AI-powered e-gamified modules in science. 80 Samples were chosen by employing purposive sampling technique. The researcher has used standardized PhET simulation modules. The results show that the post-test mean scores of the experimental group are significantly different than that of the control group. The study suggests that when students are exposed to AI-powered gamified learning environments, they develop a more positive disposition toward scientific methods and show measurable improvements in performance. This research highlights the potential of AI in transforming traditional education by making learning more dynamic, personalized, and effective, thereby fostering a deeper understanding of science and its applications.
Data Science For Healthcare
DOWNLOAD
Author : Sergio Consoli
language : en
Publisher: Springer
Release Date : 2019-02-23
Data Science For Healthcare written by Sergio Consoli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-23 with Computers categories.
This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.