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Rising Threats in Expert Applications and Solutions

Proceedings of FICR-TEAS 2020

Specificaties
Paperback, blz. | Engels
Springer Nature Singapore | e druk, 2020
ISBN13: 9789811560132
Rubricering
Springer Nature Singapore e druk, 2020 9789811560132
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

This book presents high-quality, peer-reviewed papers from the FICR International Conference on Rising Threats in Expert Applications and Solutions 2020, held at IIS University Jaipur, Rajasthan, India, on January 17–19, 2020. Featuring innovative ideas from researchers, academics, industry professionals and students, the book covers a variety of topics, including expert applications and artificial intelligence/machine learning; advanced web technologies, like IoT, big data, and cloud computing in expert applications; information and cybersecurity threats and solutions; multimedia applications in forensics, security and intelligence; advances in app development; management practices for expert applications; and social and ethical aspects of expert applications in applied sciences. 

Specificaties

ISBN13:9789811560132
Taal:Engels
Bindwijze:paperback
Uitgever:Springer Nature Singapore

Inhoudsopgave

Sentiment Analysis on E-learning using Machine Learning Classifiers in Python.- Assessment of needless code in a program.- Query caching technique over cloud based mapreduce system: a survey.- Fuzzy K-means Clutering In Measuring Course Outcome Attainment System For Higher Educational Institutes.- A Review And Comparative Study Of Frameworks For E-Commerce Application Service Onto The Public Cloud Environment.- An Implementation Of Privacy-Preserving “IF THEN ELSE” Rules For Vertically Partitioned Data.- An essential E-Governance framework for Knowledge discovery.- Vulnerability and mitigation strategies for secure expert systems.- Developing a quality model to study the impact of variability over the reusability and maintainability of software product line variabilty models.- Chunker For Gujarati Language Using Hybrid Approach.

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