Details
Title | Advances in data mining and database management (ADMDM) book series. — Modern technologies for big data classification and clustering |
---|---|
Other creators | Seetha Hari; Murty M. Narasimha,; Tripathy B. K., |
Collection | Электронные книги зарубежных издательств; Общая коллекция |
Subjects | Big data.; Data mining.; Cluster analysis.; Classification — Nonbook materials.; Document clustering.; COMPUTERS — Databases — Data Mining.; EBSCO eBooks |
Document type | Other |
File type | |
Language | English |
Rights | Доступ по паролю из сети Интернет (чтение, печать, копирование) |
Record key | ocn988619713 |
Record create date | 5/10/2017 |
Allowed Actions
pdf/1559785.pdf | – |
Action 'Read' will be available if you login or access site from another network
Action 'Download' will be available if you login or access site from another network
|
---|---|---|
epub/1559785.epub | – |
Action 'Download' will be available if you login or access site from another network
|
Group | Anonymous |
---|---|
Network | Internet |
"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.
Network | User group | Action |
---|---|---|
ILC SPbPU Local Network | All |
|
Internet | Authorized users SPbPU |
|
Internet | Anonymous |
|