• PDF / 64,053,893 Bytes
• 520 Pages / 439.37 x 666.142 pts Page_size
• 60 Downloads / 212 Views

DOWNLOAD

REPORT

Communications in Computer and Information Science

Applied Informatics Third International Conference, ICAI 2020 Ota, Nigeria, October 29–31, 2020 Proceedings

1277

Communications in Computer and Information Science Commenced Publication in 2007 Founding and Former Series Editors: Simone Diniz Junqueira Barbosa, Phoebe Chen, Alfredo Cuzzocrea, Xiaoyong Du, Orhun Kara, Ting Liu, Krishna M. Sivalingam, Dominik Ślęzak, Takashi Washio, Xiaokang Yang, and Junsong Yuan

Editorial Board Members Joaquim Filipe Polytechnic Institute of Setúbal, Setúbal, Portugal Ashish Ghosh Indian Statistical Institute, Kolkata, India Igor Kotenko St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg, Russia Raquel Oliveira Prates Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil Lizhu Zhou Tsinghua University, Beijing, China

1277

More information about this series at http://www.springer.com/series/7899

Hector Florez Sanjay Misra (Eds.) •

Applied Informatics Third International Conference, ICAI 2020 Ota, Nigeria, October 29–31, 2020 Proceedings

123

Editors Hector Florez Universidad Distrital Francisco Jose de Caldas Bogota, Colombia

Sanjay Misra Covenant University Ota, Nigeria

ISSN 1865-0929 ISSN 1865-0937 (electronic) Communications in Computer and Information Science ISBN 978-3-030-61701-1 ISBN 978-3-030-61702-8 (eBook) https://doi.org/10.1007/978-3-030-61702-8 © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

The Third International Conference on Applied Informatics (ICAI 2020) aimed to bring together researchers and practitioners working in different domains in the field of informatics in or

Recommend Documents

A new recommender system to combine content-based and collaborative filtering systems

168 106 349KB

Neural embedding collaborative filtering for recommender systems

213 35 1MB

Towards Poisoning the Neural Collaborative Filtering-Based Recommender Systems

183 18 48MB

Preference relation based collaborative filtering with graph aggregation for group recommender system

169 74 1MB

A Deep Learning Approach of Collaborative Filtering to Recommender System with Opinion Mining

201 90 29MB

A Novel Clustering Based Collaborative Filtering Recommendation System Algorithm

206 101 2MB

Balanced Accuracy of Collaborative Recommender System

203 34 27MB

Simulation Study on E-commerce Recommender System Based on a Customer-Product Purchase-Matrix

172 26 253KB

A collaborative filtering recommendation algorithm based on normalization approach

203 31 2MB

Artificial Immune System for Collaborative Spam Filtering

170 18 8MB

A Knowledge Based Recommender System Based on Consistent Preference Relations

183 42 4MB

Development of an AI Recommender System to Recommend Concerts Based on Microservice Architecture Using Collaborative and

220 82 55MB