nach der Bestellung gedruckt Neuware - Printed after ordering - 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.

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Detalles bibliogr�ficos

T�tulo: Data Mining Approaches for Big Data and Sentiment Analysis in Social Media
Editor: Engineering Science Reference
Fecha de publicaci�n: 2021
Idioma: Ingl�s
ISBN 10: 1799884139
ISBN 13: 9781799884132
Encuadernaci�n: Buch
Estado: Neu
Dimensiones: 260�mil�metros de ancho por 183 de alto por 23 de largo
Peso: 828 gramos

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Sinopsis

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.

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B. B. Gupta received his PhD degree from the Indian Institute of Technology Roorkee, India in the area of information security. He has published more than 50 research papers in international journals and conferences of high repute. He has visited several countries to present his research work. His biography has published in the Marquis Who’s Who in the World, 2012. At present, he is working as an Assistant Professor in the Department of Computer Engineering, National Institute of Technology Kurukshetra, India. His research interest includes information security, cyber security, cloud computing, web security, intrusion detection, computer networks and phishing.

Dragan Peraković received a B.Sc. degree in 1995, an M.Sc. degree in 2003, and a PhD in 2005, all at the University of Zagreb, Croatia, EU. Dragan is Head of the Department for Information and Communication Traffic and Head of Chair of Information Communication Systems and Services Management, all at the Faculty of Transport and Traffic Sciences, University of Zagreb, where he is currently a full professor. Dragan is visiting professor at the University of Mostar, Faculty of Science and Education Sciences, Mostar / Bosnia and Herzegovina. Area of scientific interests and activities is modelling of innovative communication ecosystems in the environment of the transport system (ITS) and Industry 4.0; AI & ML in cybersecurity, DDoS, Internet of Things; AI in e-forensic of communication ecosystems (terminal devices/services); design and development of new innovative services and modules.

Ahmed A. Abd El-Latif received the B.Sc. degree with honor rank in Mathematics and Computer Science in 2005 and M.Sc. degree in Computer Science in 2010, all from Menoufia University, Egypt. He received his Ph. D. degree in Computer Science & Technology at Harbin Institute of Technology (H.I.T), Harbin, P. R. China in 2013. He is an associate professor of Computer Science at Menoufia University, Egypt. He is author and co-author of more than 130 papers in reputable journal and conferences. He received many awards, State Encouragement Award in Engineering Sciences 2016, Arab Republic of Egypt; the best Ph.D student award from Harbin Institute of Technology, China 2013; Young scientific award, Menoufia University, Egypt 2014. He is a fellow at Academy of Scientific Research and Technology, Egypt. His areas of interests are multimedia content encryption, secure wireless communication, IoT, applied cryptanalysis, perceptual cryptography, secret media sharing, information hiding, biometrics, forensic analysis in digital images, and quantum information processing. Dr. Abd El-Latif is an associate editor of Journal of Cyber Security and Mobility, and Mathematical Problems in Engineering.

Deepak Gupta received his Master of Science degree from Illinois Institute of Technology, Chicago, USA, in the area of Computer Forensics and Cyber Security with a specialization in Voice Over Internet Protocol (VOIP). As an undergraduate student, he became certified on the major networking platforms, first as a CCNA (Cisco Certified Network Administrator) and then as a MCP (Microsoft Certified Professional) which would come to serve him well in his professional life. As a graduate student, Deepak continued to challenge himself by working on a number of research papers and projects related to Computer Network Security and Forensics Research, including the topics of multi-boot computer systems with change of boot loader and MP3 steganography. He also developed and furthered his interest in VOIP technology by working on and leading research projects with Bell Labs, a prominent VOIP research lab based in Chicago. Deepak also wrote research papers in this field on the topics of P2P communication and SIP protocols which won him the best student VOIP project award in 2007. Over the last 10 years of professional experience, Deepak has gained a broad range of experience in computer security and technology that spans multiple fields and industries. After graduating with distinction with a MS in Computer Science, Deepak went on to work for Sageworks, a financial software company based in Raleigh, NC. There, among other things, he developed a centralized integration process for core banking platforms that would allow customers to easily port and map their data to the central banking database. Deepak is a product visionary who founded a web agency and two other startups as a software entrepreneur to help businesses to simplify their user communication. It was during this time that Deepak's passion for innovation and entrepreneurship led him to found LoginRadius, a cloud identity and access management (cIAM) SaaS platform that helps businesses improve and optimize their customer experience by creating unified digital identities across multiple touch points, where he remains today as co-founder and CTO. At LoginRadius, Deepak makes use of his expertise in security and forensics to innovate and improve how identity services are delivered and secured in the cloud identity space and helps businesses deliver social media integrations by a simplified REST API. Currently, LoginRadius is a leading provider of cloud-based CIAM solutions for mid-to-large sized companies, and the platform serves over 3,000 businesses with a monthly reach of 850 million users worldwide. The company has been named as an industry leader in the cIAM space by Gartner, Forrester, Kuppingercole, and Computer Weekly. Deepak is also passionate about helping businesses improve and optimize their customer experience. He lives and breathes this topic with customers everyday by helping them think through questions such as how do users interact with their website, how to simplify the customer's experience (via single sign-on, one touch login, etc.), and how to keep the customer's data secure. Deepak is active member of IEEE, ACM, OpenID Foundation, Cloud Security Alliance (CSA), etc. tech communities. Deepak is doing his current research in Machine Learning, Artificial Intelligence and Blockchain Technologies. Web: www.loginradius.com

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