Data management, analytics and innovation : proceedings of ICDMAI 2020. Volume 2 / Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, Jan Martinovic, editors.
2021
QA76.9.D3 I58 2020eb
Linked e-resources
Linked Resource
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Data management, analytics and innovation : proceedings of ICDMAI 2020. Volume 2 / Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, Jan Martinovic, editors.
Meeting Name
ISBN
9789811556197 (electronic bk.)
9811556199 (electronic bk.)
9811556180
9789811556180
9811556199 (electronic bk.)
9811556180
9789811556180
Published
Singapore : Springer, [2021]
Language
English
Description
1 online resource (454 pages)
Item Number
10.1007/978-981-15-5
Call Number
QA76.9.D3 I58 2020eb
Dewey Decimal Classification
005.74
Summary
This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17-19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Note
International conference proceedings.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Series
Advances in intelligent systems and computing ; 1175.
Available in Other Form
Linked Resources
Record Appears in
Table of Contents
Automatic Standardization of Data based on Machine Learning and Natural Language Processing
Scoring Algorithm Identifying Anomalous Behavior in Enterprise Network.-APPLICATION OF BAYESIAN AUTOMATED HYPERPARAMETER TUNING ON CLASSIFIERS PREDICTING CUSTOMER RETENTION IN BANKING INDUSTRY
Quantum Machine Learning: A Review and Current Status
Survey of Transfer Learning and a Case Study of Emotion Recognition using Inductive Approach
An Efficient Algorithm for Complete Linkage Clustering with a Merging Threshold.
Scoring Algorithm Identifying Anomalous Behavior in Enterprise Network.-APPLICATION OF BAYESIAN AUTOMATED HYPERPARAMETER TUNING ON CLASSIFIERS PREDICTING CUSTOMER RETENTION IN BANKING INDUSTRY
Quantum Machine Learning: A Review and Current Status
Survey of Transfer Learning and a Case Study of Emotion Recognition using Inductive Approach
An Efficient Algorithm for Complete Linkage Clustering with a Merging Threshold.