Advances in Big Data Analytics (Record no. 178797)
[ view plain ]
000 -LEADER | |
---|---|
fixed length control field | 03661nam a22005415i 4500 |
001 - CONTROL NUMBER | |
control field | 978-981-16-3607-3 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20240423125521.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
fixed length control field | cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 220113s2022 si | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9789811636073 |
-- | 978-981-16-3607-3 |
024 7# - OTHER STANDARD IDENTIFIER | |
Standard number or code | 10.1007/978-981-16-3607-3 |
Source of number or code | doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | Q336 |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UN |
Source | bicssc |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | COM021000 |
Source | bisacsh |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UN |
Source | thema |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 005.7 |
Edition number | 23 |
100 1# - MAIN ENTRY--PERSONAL NAME | |
Personal name | Shi, Yong. |
Relator term | author. |
Relator code | aut |
-- | http://id.loc.gov/vocabulary/relators/aut |
245 10 - TITLE STATEMENT | |
Title | Advances in Big Data Analytics |
Medium | [electronic resource] : |
Remainder of title | Theory, Algorithms and Practices / |
Statement of responsibility, etc | by Yong Shi. |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2022. |
264 #1 - | |
-- | Singapore : |
-- | Springer Nature Singapore : |
-- | Imprint: Springer, |
-- | 2022. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | XIV, 728 p. 1 illus. |
Other physical details | online resource. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
-- | |
-- | rda |
505 0# - FORMATTED CONTENTS NOTE | |
Formatted contents note | Part One: Concept and Theoretical Foundation -- Chapter 1: Big Data and Big Data Analytics -- Chapter 2: Multiple Criteria Optimization Classification -- Chapter 3: Support Vector Machine Classification -- Part Two: Functional Analysis -- Chapter 4: Feature Selection -- Chapter 5: Data Stream Analysis -- Chapter 6: Learning Analysis -- Chapter 7: Sentiment Analysis -- Chapter 8: Link Analysis -- Chapter 9: Evaluation Analysis -- Part Three: Application and Future Analysis -- Chapter 10: Business and Engineering Applications -- Chapter 11: Healthcare Applications -- Chapter 12: Artificial Intelligence IQ Test -- Chapter 13: Conclusions. |
520 ## - SUMMARY, ETC. | |
Summary, etc | Today, big data affects countless aspects of our daily lives. This book provides a comprehensive and cutting-edge study on big data analytics, based on the research findings and applications developed by the author and his colleagues in related areas. It addresses the concepts of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines for classification, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis. The book also explores lessons learned in applying big data to business, engineering and healthcare. Lastly, it addresses the advanced topic of intelligence-quotient (IQ) tests for artificial intelligence. Since each aspect mentioned above concerns a specific domain of application, taken together, the algorithms, procedures, analysis and empirical studies presented here offer a general picture of big data developments. Accordingly, the book can not only serve as a textbook for graduates with a fundamental grasp of training in big data analytics, but can also show practitioners how to use the proposed techniques to deal with real-world big data problems. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial intelligence |
General subdivision | Data processing. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Big data. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Data mining. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Computer science. |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Data Science. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Big Data. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Data Mining and Knowledge Discovery. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Models of Computation. |
710 2# - ADDED ENTRY--CORPORATE NAME | |
Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY | |
Title | Springer Nature eBook |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9789811636066 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9789811636080 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9789811636097 |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-981-16-3607-3">https://doi.org/10.1007/978-981-16-3607-3</a> |
912 ## - | |
-- | ZDB-2-SCS |
912 ## - | |
-- | ZDB-2-SXCS |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks-CSE-Springer |
No items available.