Noise Filtering for Big Data Analytics / (Record no. 84513)

000 -LEADER
fixed length control field 06958nam a22010575i 4500
001 - CONTROL NUMBER
control field 9783110697216
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730161642.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230529t20222022gw fo d z eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783110697216
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Language code of text/sound track or separate title
082 04 - CLASSIFICATION NUMBER
Call Number 004
245 00 - TITLE STATEMENT
Title Noise Filtering for Big Data Analytics /
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource (VIII, 156 p.)
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Series statement De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences ,
520 ## - SUMMARY, ETC.
Summary, etc This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model. Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information. This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.
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Author 2 Acharjee, Santanu,
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Author 2 Bhattacharyya, Souvik,
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Author 2 Bhattacharyya, Souvik,
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Author 2 Chaudhuri, Dipta,
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Author 2 Dawud Adebayo, Agunbiade,
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Author 2 Ghosh, Koushik,
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Author 2 Ghosh, Koushik,
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Author 2 Indu, Pabak,
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Author 2 Khan, Samarpita,
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Author 2 Khondekar, Mofazzal H.,
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Author 2 Mukherjee, Moloy,
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Author 2 Nureni Olawale, Adeboye,
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Author 2 Paul, Rimi,
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Author 2 Purkait, Souvik,
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Author 2 Saha, Gokul,
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Author 2 Samadder, Swetadri,
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Author 2 Sengupta, Anindita,
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Author 2 Sharma, Vivek,
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Author 2 Singh, Vijai,
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1515/9783110697216
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.degruyter.com/isbn/9783110697216
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.degruyter.com/document/cover/isbn/9783110697216/original
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-- Berlin ;
-- Boston :
-- De Gruyter,
-- [2022]
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-- ©2022
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-- text
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-- computer
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-- rdamedia
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-- online resource
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-- text file
-- PDF
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-- Description based on online resource; title from PDF title page (publisher's Web site, viewed 29. Mai 2023)
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-- Angewandte Mathematik.
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-- Big Data.
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-- Künstliche Intelligenz.
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-- Maschinelles Lernen.
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-- COMPUTERS / Information Technology.
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-- 978-3-11-076682-0 DG Plus DeG Package 2022 Part 1
-- 2022
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-- 978-3-11-099389-9 EBOOK PACKAGE COMPLETE 2022 English
-- 2022
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-- 978-3-11-099422-3 EBOOK PACKAGE Engineering, Computer Sciences 2022 English
-- 2022
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-- 2022

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