UID:
almahu_9949709215102882
Format:
XXIII, 681 p. 194 illus., 140 illus. in color.
,
online resource.
Edition:
1st ed. 2024.
ISBN:
9783031456459
Series Statement:
Lecture Notes in Networks and Systems, 800
Content:
This book is composed of a selection of articles from the 11st World Conference on Information Systems and Technologies, held between 4 and 5 of April 2023, at Sant'Anna School of Advanced Studies, in Pisa, Italy. WorldCIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences, and challenges of modern Information Systems and Technologies research, together with their technological development and applications. The main and distinctive topics covered are: A) Information and Knowledge Management; B) Organizational Models and Information Systems; C) Software and Systems Modeling; D) Software Systems, Architectures, Applications, and Tools; E) Multimedia Systems and Applications; F) Computer Networks, Mobility, and Pervasive Systems; G) Intelligent and Decision Support Systems; H) Big Data Analytics and Applications; I) Human-Computer Interaction; J) Ethics, Computers, and Security; K) Health Informatics; L) Information Technologies in Education; M) Information Technologies in Radiocommunications; and N) Technologies for Biomedical Applications.
Note:
Knowledge discovery in wikidata with machine learning in graph -- Topic Modelling for Detecting Reactions to Science Communication on Social Networks -- Pragmatic Statistics: Likert-Type Questionnaires Processing -- The influence of knowing the source of information on reader's perceptions. An exploratory study on Twitter -- Knowledge Management: A new business success factor in companies in southern Peru -- Relationship Between Subjective Wellbeing and Prosocial Activities (Ecuadorian Case) -- The data repositories in agriculture. A preliminary investigation -- Towards a KOS to Manage and Retrieve Legal Data -- Experimental Analyses of Temporal Activity-Sequencing Anomalies in Process Mining -- Supervised Machine Learning Based Anomaly Detection in Online Social Networks.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783031456442
Additional Edition:
Printed edition: ISBN 9783031456466
Language:
English
DOI:
10.1007/978-3-031-45645-9
URL:
https://doi.org/10.1007/978-3-031-45645-9
URL:
Volltext
(URL des Erstveröffentlichers)
Bookmarklink
