Data Mining Approaches for Big Data and Sentiment Analysis in Social Media

ISBN 10: 1799884139 ISBN 13: 9781799884132
Verlag: Engineering Science Reference, 2021
Neu Hardcover

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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explores 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.Klapp. Bestandsnummer des Verkäufers 531707664

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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.

Über die Autorin bzw. den Autor: 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.

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Titel: Data Mining Approaches for Big Data and ...
Verlag: Engineering Science Reference
Erscheinungsdatum: 2021
Einband: Hardcover
Zustand: New

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ISBN 10: 1799884139 ISBN 13: 9781799884132
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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 336 | Sprache: Englisch | Produktart: Bücher | 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. Artikel-Nr. 38257850/1

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