Data Management, Analytics and Innovation : Proceedings of ICDMAI 2021, Volume 1 / / edited by Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, Alfred M. Bruckstein

• Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021
• Edizione: 1st ed. 2021.
• Descrizione fisica: 1 online resource (453 pages)
• Disciplina: 005.74
• Soggetto topico: Computational intelligence; Engineering - Data processing; Big data; Computational Intelligence; Data Engineering; Big Data
• Persona (resp. second.): SharmaNeha (Of Tufts University. School of Medicine)
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Verification, Validation and Evaluation of Medicinal Prescription System -- Creation of Knowledge Graph for Client complaint Management System -- Automation of Bid Proposal Preparation through AI Smart Assistant -- A Review on Application of Machine Learning and Deep Learning Algorithms in Head and Neck Cancer Prediction and Prognosis -- Multi-Index Validation Mechanisms for the Land Cover Classification of Multispectral Images: A Case-Study of Kabini Reservoir -- Optimizing the reliability of a bank with Logistic Regression and Particle Swarm Optimization -- Performance Evaluation of Classification Models for HIV/AIDS Dataset -- Impact of clustering algorithms in catastrophe management: a task-technology appropriate perspective -- Real-Time Soybean Crop Insect Classification using Customized Deep Learning Models -- Writer-independent Offline Signature Verification using Deep Siamese Neural Network.
• Sommario/riassunto: This book presents the latest findings in the areas of data management and smart computing, machine learning, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at Fifth International Conference on Data Management, Analytics and Innovation (ICDMAI 2021), held during January 15–17, 2021, in a virtual mode. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
• Titolo autorizzato: Data Management, Analytics and Innovation
• ISBN: 9789811629341; 981162934X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910495181403321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes on Data Engineering and Communications Technologies, . 2367-4520 ; ; 70