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Big data analytics for sustainable computing Advances in data mining and database management (ADMDM) book series./ [edited by] Anandakumar Haldorai, Arulmurugan Ramu.
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| dc.contributor.author | Haldorai Anandakumar | |
| dc.contributor.author | Ramu Arulmurugan | |
| dc.date.accessioned | 2024-01-29T21:40:34Z | |
| dc.date.available | 2024-01-29T21:40:34Z | |
| dc.date.issued | 2020 | |
| dc.identifier.citation | Big data analytics for sustainable computing Advances in data mining and database management (ADMDM) book series. - 1 online resource. - URL: https://libweb.kpfu.ru/ebsco/pdf/2257549.pdf | |
| dc.identifier.isbn | 9781522597520 | |
| dc.identifier.isbn | 1522597522 | |
| dc.identifier.uri | https://dspace.kpfu.ru/xmlui/handle/net/179736 | |
| dc.description | Includes bibliographical references and index. | |
| dc.description.abstract | Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative rese. | |
| dc.description.tableofcontents | Chapter 1. Understanding big data -- Chapter 2. A detailed study on classification algorithms in big data -- Chapter 3. Big data and analytics -- Chapter 4. Decoding big data analytics for emerging business through data-intensive applications and business intelligence: a review on analytics applications and theoretical aspects -- Chapter 5. Feature selection algorithm using relative odds for data mining classification -- Chapter 6. Social network analysis -- Chapter 7. Role of machine intelligence and big data in remote sensing -- Chapter 8. Provisioning system for application virtualization environments -- Chapter 9. Big data-based spectrum sensing for cognitive radio networks using artificial intelligence -- Chapter 10. Big data analytics in the healthcare industry: an analysis of healthcare applications in machine learning with big data analytics -- Chapter 11. Big data analytics and visualization for food health status determination using bigmart data -- Chapter 12. "Saksham model" performance improvisation using Node capability evaluation in apache hadoop. | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.relation.ispartofseries | Advances in Data Mining and Database Management (ADMDM) Book Series | |
| dc.relation.ispartofseries | Advances in data mining and database management (ADMDM) book series. | |
| dc.subject.other | Big data. | |
| dc.subject.other | Big data. | |
| dc.subject.other | Electronic books. | |
| dc.title | Big data analytics for sustainable computing Advances in data mining and database management (ADMDM) book series./ [edited by] Anandakumar Haldorai, Arulmurugan Ramu. | |
| dc.type | Book | |
| dc.contributor.org | IGI Global, | |
| dc.description.pages | 1 online resource. | |
| dc.collection | Электронно-библиотечные системы | |
| dc.source.id | EN05CEBSCO05C424 |
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