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1.
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Z 62
Zhizhin, (Gennadiĭ Vladimirovich),.
Nanotechnologies and clusters in the spaces of higher dimension : : emerging research and opportunities / / Gennadiy Vladimirovich Zhizhin. - Hershey, PA : : Engineering Science Reference, an imprint of IGI Global,, [2021]. - 1 online resource (xvi, 286 pages) : : il. - (Advances in chemical and materials engineering (ACME) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/2F4B58C4-D996-464A-B3AA-9FE6EAED3A5F. - ISBN 1799837858 (electronic book). - ISBN 9781799837855 (electronic bk.)
"Research Insights" -- taken from front cover. Description based on online resource; title from digital title page (viewed on October 01, 2020).
Параллельные издания: Print version: : Zhizhin, G. V. (Gennadiĭ Vladimirovich). Nanotechnologies and clusters in the spaces of higher dimension. - Hershey, PA : Engineering Science Reference, an imprint of IGI Global, [2020]. - ISBN 9781799837848
Содержание:
Chapter 1. Higher-dimensional space of nanoworld -- Chapter 2. Higher dimensions of clusters of intermetallic compounds -- Chapter 3. Dimension of chemical compounds of atoms metals with atoms no metals -- Chapter 4. Chains of metallic clusters with ligands -- Chapter 5. Closed metal cycles in clusters with ligands -- Chapter 6. Metallic clusters with ligands and polyhedral core -- Chapter 7. Incident conservation law -- Chapter 8. Mathematical design of nanomaterials from clusters of higher dimension -- Chapter 9. Nanostructures as tillings of higher dimension spaces.
~РУБ DDC 620/.50151953
Рубрики: Nanotechnology--Mathematics.
Quasicrystals.
Cluster analysis.
Cluster analysis.
Quasicrystals.
Аннотация: "This book examines nanotechnologies and clusters in the spaces of higher dimension"--
Z 62
Zhizhin, (Gennadiĭ Vladimirovich),.
Nanotechnologies and clusters in the spaces of higher dimension : : emerging research and opportunities / / Gennadiy Vladimirovich Zhizhin. - Hershey, PA : : Engineering Science Reference, an imprint of IGI Global,, [2021]. - 1 online resource (xvi, 286 pages) : : il. - (Advances in chemical and materials engineering (ACME) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/2F4B58C4-D996-464A-B3AA-9FE6EAED3A5F. - ISBN 1799837858 (electronic book). - ISBN 9781799837855 (electronic bk.)
"Research Insights" -- taken from front cover. Description based on online resource; title from digital title page (viewed on October 01, 2020).
Параллельные издания: Print version: : Zhizhin, G. V. (Gennadiĭ Vladimirovich). Nanotechnologies and clusters in the spaces of higher dimension. - Hershey, PA : Engineering Science Reference, an imprint of IGI Global, [2020]. - ISBN 9781799837848
Содержание:
Chapter 1. Higher-dimensional space of nanoworld -- Chapter 2. Higher dimensions of clusters of intermetallic compounds -- Chapter 3. Dimension of chemical compounds of atoms metals with atoms no metals -- Chapter 4. Chains of metallic clusters with ligands -- Chapter 5. Closed metal cycles in clusters with ligands -- Chapter 6. Metallic clusters with ligands and polyhedral core -- Chapter 7. Incident conservation law -- Chapter 8. Mathematical design of nanomaterials from clusters of higher dimension -- Chapter 9. Nanostructures as tillings of higher dimension spaces.
Рубрики: Nanotechnology--Mathematics.
Quasicrystals.
Cluster analysis.
Cluster analysis.
Quasicrystals.
Аннотация: "This book examines nanotechnologies and clusters in the spaces of higher dimension"--
2.
Подробнее
M 78
Modern technologies for big data classification and clustering / / Hari Seetha, Vellore Institute of Technology-Andhra Pradesh, India ; M. Narasimha Murty, Indian Institute of Science, India ; B. K. Tripathy, VIT University, India. - Hershey, PA : : IGI Global,, ©2018. - 1 online resource (xxi, 360 pages) : : il. - (Advances in data mining and database management (ADMDM) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/383A8125-3F23-41B5-9C60-C61262DE4593. - ISBN 9781522528067 (electronic bk.). - ISBN 1522528067 (electronic bk.)
Description based on print version record
Параллельные издания: Print version: : Modern technologies for big data classification and clustering. - Hershey, PA : Information Science Reference, [2018]. - ISBN 9781522528050
Содержание:
Uncertainty-based clustering algorithms for large data sets / B. K. Tripathy, Hari Seetha, M. N. Murty -- Sentiment mining approaches for big data classification and clustering / Ashok Kumar J, Abirami S, Tina Esther Trueman -- Data compaction techniques / R. Raj Kumar, P. Viswanath, C. Shoba Bindu -- Methodologies and technologies to retrieve information from text sources / Anu Singha, Phub Namgay -- Twitter data analysis / Chitrakala S -- Use of social network analysis in telecommunication domain / Sushruta Mishra, Hrudaya Kumar Tripathy, Monalisa Mishra, Bijayalaxmi Panda -- A review on spatial big data analytics and visualization / Bangaru Kamatchi Seethapathy, Parvathi R -- A survey on overlapping communities in large-scale social networks / S Rao Chintalapudi, H. M. Krishna Prasad -- A brief study of approaches to text feature selection / Ravindra Babu Tallamaraju, Manas Kirti -- Biological big data analysis and visualization: a survey / Vignesh U, Parvathi R
~РУБ DDC 005.7
Рубрики: Big data.
Data mining.
Cluster analysis.
Classification--Nonbook materials.
Document clustering.
COMPUTERS--Databases--Data Mining.
Big data.
Classification--Nonbook materials.
Cluster analysis.
Data mining.
Document clustering.
Аннотация: "This book provides an analysis of large data in the field of classification and clustering by presenting algorithms and comparative analysis in the form of their effectiveness and efficiency. It covers topics such as handling large data with conventional data mining, machine learning algorithms and information about new technologies, algorithms and platforms developed for handling large data"--
Data has increased due to the growing use of web applications and communication devices. It is necessary to develop new techniques of managing data in order to ensure adequate usage. Modern Technologies for Big Data Classification and Clustering is an essential reference source for the latest scholarly research on handling large data sets with conventional data mining and provide information about the new technologies developed for the management of large data. Featuring coverage on a broad range of topics such as text and web data analytics, risk analysis, and opinion mining, this publication is ideally designed for professionals, researchers, and students seeking current research on various concepts of big data analytics.
Доп.точки доступа:
Seetha, Hari, (1970-) \editor.\
Murty, M. Narasimha, \editor.\
Tripathy, B. K., (1957-) \editor.\
M 78
Modern technologies for big data classification and clustering / / Hari Seetha, Vellore Institute of Technology-Andhra Pradesh, India ; M. Narasimha Murty, Indian Institute of Science, India ; B. K. Tripathy, VIT University, India. - Hershey, PA : : IGI Global,, ©2018. - 1 online resource (xxi, 360 pages) : : il. - (Advances in data mining and database management (ADMDM) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/383A8125-3F23-41B5-9C60-C61262DE4593. - ISBN 9781522528067 (electronic bk.). - ISBN 1522528067 (electronic bk.)
Description based on print version record
Параллельные издания: Print version: : Modern technologies for big data classification and clustering. - Hershey, PA : Information Science Reference, [2018]. - ISBN 9781522528050
Содержание:
Uncertainty-based clustering algorithms for large data sets / B. K. Tripathy, Hari Seetha, M. N. Murty -- Sentiment mining approaches for big data classification and clustering / Ashok Kumar J, Abirami S, Tina Esther Trueman -- Data compaction techniques / R. Raj Kumar, P. Viswanath, C. Shoba Bindu -- Methodologies and technologies to retrieve information from text sources / Anu Singha, Phub Namgay -- Twitter data analysis / Chitrakala S -- Use of social network analysis in telecommunication domain / Sushruta Mishra, Hrudaya Kumar Tripathy, Monalisa Mishra, Bijayalaxmi Panda -- A review on spatial big data analytics and visualization / Bangaru Kamatchi Seethapathy, Parvathi R -- A survey on overlapping communities in large-scale social networks / S Rao Chintalapudi, H. M. Krishna Prasad -- A brief study of approaches to text feature selection / Ravindra Babu Tallamaraju, Manas Kirti -- Biological big data analysis and visualization: a survey / Vignesh U, Parvathi R
Рубрики: Big data.
Data mining.
Cluster analysis.
Classification--Nonbook materials.
Document clustering.
COMPUTERS--Databases--Data Mining.
Big data.
Classification--Nonbook materials.
Cluster analysis.
Data mining.
Document clustering.
Аннотация: "This book provides an analysis of large data in the field of classification and clustering by presenting algorithms and comparative analysis in the form of their effectiveness and efficiency. It covers topics such as handling large data with conventional data mining, machine learning algorithms and information about new technologies, algorithms and platforms developed for handling large data"--
Data has increased due to the growing use of web applications and communication devices. It is necessary to develop new techniques of managing data in order to ensure adequate usage. Modern Technologies for Big Data Classification and Clustering is an essential reference source for the latest scholarly research on handling large data sets with conventional data mining and provide information about the new technologies developed for the management of large data. Featuring coverage on a broad range of topics such as text and web data analytics, risk analysis, and opinion mining, this publication is ideally designed for professionals, researchers, and students seeking current research on various concepts of big data analytics.
Доп.точки доступа:
Seetha, Hari, (1970-) \editor.\
Murty, M. Narasimha, \editor.\
Tripathy, B. K., (1957-) \editor.\
Page 1, Results: 2