Developing a Keyword Extractor and Document Classifier: Emerging Research and Opportunities
Developing a Keyword Extractor and Document Classifier: Emerging Research and Opportunities

Author: Paul, Dimple Valayil

Publisher: IGI Global

Published: 2021-01-08

Total Pages: 229

ISBN-13: 1799837734

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The main problems that prevent fast and high-quality document processing in electronic document management systems are insufficient and unstructured information, information redundancy, and the presence of large amounts of undesirable user information. The human factor has a significant impact on the efficiency of document search. An average user is not aware of the advanced option of a query language and uses typical queries. Development of a specialized software toolkit intended for information systems and electronic document management systems can be an effective solution of the tasks listed above. Such toolkits should be based on the means and methods of automatic keyword extraction and text classification. The categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years due to the increased availability of documents in digital form and the ensuing need to organize them. Thus, research on keyword extraction, advancements in the field, and possible future solutions is of great importance in current times. Developing a Keyword Extractor and Document Classifier: Emerging Research and Opportunities presents an information extraction mechanism that can process many kinds of inputs, realize the type of text, and understand the percentage of the keywords that has to be stored. This mechanism then supports information extraction and information categorization mechanisms. This module is used to support a text summarization mechanism, which leads—with the help of the keyword extraction module—to text categorization. It employs lexical and information retrieval techniques to extract phrases from the document text that are likely to characterize it and determines the category of the retrieved text to present a summary to the users. This book is ideal for practitioners, stakeholders, researchers, academicians, and students who are interested in the development of a new keyword extractor and document classifier method.

New Opportunities for Sentiment Analysis and Information Processing
New Opportunities for Sentiment Analysis and Information Processing

Author: Sharaff, Aakanksha

Publisher: IGI Global

Published: 2021-06-25

Total Pages: 311

ISBN-13: 179988063X

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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.

Applications of Big Data in Large- and Small-Scale Systems
Applications of Big Data in Large- and Small-Scale Systems

Author: Goundar, Sam

Publisher: IGI Global

Published: 2021-01-15

Total Pages: 377

ISBN-13: 1799866750

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With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

Industry Use Cases on Blockchain Technology Applications in IoT and the Financial Sector
Industry Use Cases on Blockchain Technology Applications in IoT and the Financial Sector

Author: Mahmood, Zaigham

Publisher: IGI Global

Published: 2021-03-18

Total Pages: 400

ISBN-13: 1799866521

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Blockchain technology presents numerous advantages that include increased transparency, reduced transaction costs, faster transaction settlement, automation of information, increased traceability, improved customer experience, improved digital identity, better cyber security, and user-controlled networks. These potential applications are widespread and diverse including funds transfer, smart contracts, e-voting, efficient supply chain, and more in nearly every sector of society including finance, healthcare, law, trade, real estate, and other important areas. However, there are challenges and limitations that exist such as high energy consumption, limited scalability, complexity, security, network size, lack of regulations, and other critical issues. Nevertheless, blockchain is an attractive technology and has much to offer to the modern-day industry. Industry Use Cases on Blockchain Technology Applications in IoT and the Financial Sector investigates blockchain technology’s adoption and effectiveness in multiple industries and for the internet of things (IoT)-based applications, presents use cases from industrial and financial sectors as well as from other transaction-based services, and fills a gap in this respect by extending the existing body of knowledge in the suggested field. While highlighting topics such as cybersecurity, use cases, and models for blockchain implementation, this book is ideal for business managers, financial accountants, practitioners, researchers, academicians, and students interested in blockchain technology’s role and implementation in IoT and the financial sector.

Intelligent Analytics With Advanced Multi-Industry Applications
Intelligent Analytics With Advanced Multi-Industry Applications

Author: Sun, Zhaohao

Publisher: IGI Global

Published: 2021-01-08

Total Pages: 392

ISBN-13: 1799849643

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Many fundamental technological and managerial issues surrounding the development and implementation of intelligent analytics within multi-industry applications remain unsolved. There are still questions surrounding the foundation of intelligent analytics, the elements, the big characteristics, and the effects on business, management, technology, and society. Research is devoted to answering these questions and understanding how intelligent analytics can improve healthcare, mobile commerce, web services, cloud services, blockchain, 5G development, digital transformation, and more. Intelligent Analytics With Advanced Multi-Industry Applications is a critical reference source that explores cutting-edge theories, technologies, and methodologies of intelligent analytics with multi-industry applications and emphasizes the integration of artificial intelligence, business intelligence, big data, and analytics from a perspective of computing, service, and management. This book also provides real-world applications of the proposed concept of intelligent analytics to e-SMACS (electronic, social, mobile, analytics, cloud, and service) commerce and services, healthcare, the internet of things, the sharing economy, cloud computing, blockchain, and Industry 4.0. This book is ideal for scientists, engineers, educators, university students, service and management professionals, policymakers, decision makers, practitioners, stakeholders, researchers, and others who have an interest in how intelligent analytics are being implemented and utilized in diverse industries.

Data Science Advancements in Pandemic and Outbreak Management
Data Science Advancements in Pandemic and Outbreak Management

Author: Asimakopoulou, Eleana

Publisher: IGI Global

Published: 2021-04-09

Total Pages: 255

ISBN-13: 1799867382

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Pandemics are disruptive. Thus, there is a need to prepare and plan actions in advance for identifying, assessing, and responding to such events to manage uncertainty and support sustainable livelihood and wellbeing. A detailed assessment of a continuously evolving situation needs to take place, and several aspects must be brought together and examined before the declaration of a pandemic even happens. Various health organizations; crisis management bodies; and authorities at local, national, and international levels are involved in the management of pandemics. There is no better time to revisit current approaches to cope with these new and unforeseen threats. As countries must strike a fine balance between protecting health, minimizing economic and social disruption, and respecting human rights, there has been an emerging interest in lessons learned and specifically in revisiting past and current pandemic approaches. Such approaches involve strategies and practices from several disciplines and fields including healthcare, management, IT, mathematical modeling, and data science. Using data science to advance in-situ practices and prompt future directions could help alleviate or even prevent human, financial, and environmental compromise, and loss and social interruption via state-of-the-art technologies and frameworks. Data Science Advancements in Pandemic and Outbreak Management demonstrates how strategies and state-of-the-art IT have and/or could be applied to serve as the vehicle to advance pandemic and outbreak management. The chapters will introduce both technical and non-technical details of management strategies and advanced IT, data science, and mathematical modelling and demonstrate their applications and their potential utilization within the identification and management of pandemics and outbreaks. It also prompts revisiting and critically reviewing past and current approaches, identifying good and bad practices, and further developing the area for future adaptation. This book is ideal for data scientists, data analysts, infectious disease experts, researchers studying pandemics and outbreaks, IT, crisis and disaster management, academics, practitioners, government officials, and students interested in applicable theories and practices in data science to mitigate, prepare for, respond to, and recover from future pandemics and outbreaks.

Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance
Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance

Author: Rana, Dipti P.

Publisher: IGI Global

Published: 2021-06-04

Total Pages: 309

ISBN-13: 1799873730

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Over the last two decades, researchers are looking at imbalanced data learning as a prominent research area. Many critical real-world application areas like finance, health, network, news, online advertisement, social network media, and weather have imbalanced data, which emphasizes the research necessity for real-time implications of precise fraud/defaulter detection, rare disease/reaction prediction, network intrusion detection, fake news detection, fraud advertisement detection, cyber bullying identification, disaster events prediction, and more. Machine learning algorithms are based on the heuristic of equally-distributed balanced data and provide the biased result towards the majority data class, which is not acceptable considering imbalanced data is omnipresent in real-life scenarios and is forcing us to learn from imbalanced data for foolproof application design. Imbalanced data is multifaceted and demands a new perception using the novelty at sampling approach of data preprocessing, an active learning approach, and a cost perceptive approach to resolve data imbalance. Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance offers new aspects for imbalanced data learning by providing the advancements of the traditional methods, with respect to big data, through case studies and research from experts in academia, engineering, and industry. The chapters provide theoretical frameworks and the latest empirical research findings that help to improve the understanding of the impact of imbalanced data and its resolving techniques based on data preprocessing, active learning, and cost perceptive approaches. This book is ideal for data scientists, data analysts, engineers, practitioners, researchers, academicians, and students looking for more information on imbalanced data characteristics and solutions using varied approaches.

Blockchain and AI Technology in the Industrial Internet of Things
Blockchain and AI Technology in the Industrial Internet of Things

Author: Pani, Subhendu Kumar

Publisher: IGI Global

Published: 2021-01-08

Total Pages: 317

ISBN-13: 1799866955

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Blockchain and artificial intelligence (AI) in industrial internet of things is an emerging field of research at the intersection of information science, computer science, and electronics engineering. The radical digitization of industry coupled with the explosion of the internet of things (IoT) has set up a paradigm shift for industrial and manufacturing companies. There exists a need for a comprehensive collection of original research of the best performing methods and state-of-the-art approaches in this area of blockchain, AI, and the industrial internet of things in this new era for industrial and manufacturing companies. Blockchain and AI Technology in the Industrial Internet of Things compares different approaches to the industrial internet of things and explores the direct impact blockchain and AI technology have on the betterment of the human life. The chapters provide the latest advances in the field and provide insights and concerns on the concept and growth of the industrial internet of things. While including research on security and privacy, supply chain management systems, performance analysis, and a variety of industries, this book is ideal for professionals, researchers, managers, technologists, security analysts, executives, practitioners, researchers, academicians, and students looking for advanced research and information on the newest technologies, advances, and approaches for blockchain and AI in the industrial internet of things.

Political and Economic Implications of Blockchain Technology in Business and Healthcare
Political and Economic Implications of Blockchain Technology in Business and Healthcare

Author: Rodrigues, Dário de Oliveira

Publisher: IGI Global

Published: 2021-06-11

Total Pages: 389

ISBN-13: 179987365X

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Besides love, money and health are the most valuable human yearnings. Therefore, blockchain technology is paramount: a new foundation of confidence for human valuable transactions. Like information sharing was catalyzed on the pre-blockchain internet, transactions are now triggered on the new internet of value. In this second digital inflection point, economic media encompasses value beside information, and individuals can privately transact digital assets for the first time in history. Decentralized but structured organizations running on blockchain networks reduce transaction costs and are particularly competitive insofar as they guarantee data authenticity, confidentiality, and integrity, providing functional autonomy with disintermediation and smart contracts. Everything changed after user data were made public on the internet and privately traded by big tech companies, and nothing will be the same once that data is made private on the internet and publicly transacted by their rightful owners. While the internet of information reshaped the world, the internet of value will reform it, and everything will depend politically on this being done freely. Political and Economic Implications of Blockchain Technology in Business and Healthcare provides relevant theoretical frameworks on the civilizational impact of blockchain technology, which redesigns human interactions concerning value transactions. It gives ideas, concepts, and instruments to advance the knowledge on cryptoeconomics and decentralized governance in the new distributed trust paradigm. The chapters explore the ethical repercussions and profound political-economic consequences to society, providing insights into business applications focusing on the healthcare sector. In a blockchain era affected by the post-COVID-19 new normal, which mixes politics, economics, and health, this book is essential for students and researchers in social and life sciences; professionals and policymakers working in the fields of public and business administration; and healthcare workers and researchers, academicians, and students interested in blockchain technology and its political and economic impacts in the industry and society.

Transforming Scholarly Publishing With Blockchain Technologies and AI
Transforming Scholarly Publishing With Blockchain Technologies and AI

Author: Gunter, Darrell Wayne

Publisher: IGI Global

Published: 2021-06-18

Total Pages: 336

ISBN-13: 1799855910

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Every industry will be positively affected by blockchain and AI technology at some point. However, blockchain is a misunderstood technology within the publishing realm. The scholarly publishing industry can significantly improve the flow of research, drive down costs, and introduce new efficiencies in the publishing industry with these new technologies. The scholarly publishing industry is in its early days of the digital transformation, and blockchain and AI technology could play a major role in this. However, the industry has been resistant to change. These reasons include but are not limited to staying with legacy systems, cost of new platforms, changing cultures, and understanding and adopting new technologies. With proper research and information provided, the publishing industry can adopt these technologies for beneficial advancements and the generation of a bright future. Transforming Scholarly Publishing With Blockchain Technologies and AI explores the changing landscape of scholarly publishing and how blockchain technologies and AI are slowly being integrated and used within the industry. This book covers both the benefits and challenges of implementing technology and provides both cases and new developments. Topics highlighted include business model developments, new efficiencies in scholarly publishing, blockchain in research libraries, knowledge discovery, and blockchain in academic publishing. This book is a valuable reference tool for publishers, IT specialists, technologists, publishing vendors, researchers, academicians, and students who are interested in how blockchain technologies and AI are transforming and developing a modern scholarly publishing industry.