Research Challenges in Information Science (eBook, PDF)

14th International Conference, RCIS 2020, Limassol, Cyprus, September 23-25, 2020, Proceedings
Redaktion: Dalpiaz, Fabiano; Loucopoulos, Pericles; Zdravkovic, Jelena

• Format: PDF

Produktbeschreibung

This book constitutes the proceedings of the 14^th International Conference on Research Challenges in Information Sciences, RCIS 2020, held in Limassol, Cyprus, during September 23-25, 2020. The conference was originally scheduled in for 2020, but the organizing committee was forced to postpone the conference due to the outbreak of the COVID-19 pandemic.

The scope of RCIS 2020 is summarized by the thematic areas of information systems and their engineering; user-oriented approaches; data and information management; business process management; domain-specific information systems engineering; data science; information infrastructures, and reflective research and practice.

The 26 full papers and 3 work in progress papers presented in this volume were carefully reviewed and selected from 106 submissions. They were organized in topical sections named:

Data Analytics and Business Intelligence; Digital Enterprise and Technologies; Human Factors in Information Systems; Information Systems Development and Testing; Machine Learning and Text Processing; and Security and Privacy. The volume also contains 12 poster and demo-papers, and 4 Doctoral Consortium papers.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 653
• Erscheinungstermin: 24. Juni 2020
• Englisch
• ISBN-13: 9783030503161
• Artikelnr.: 59752392

Inhaltsangabe

Data Analytics and Business Intelligence.- Toward Becoming a Data-Driven Organization: Challenges and Benefits.- A Big Data Conceptual Model to Improve Quality of Business Analytics.- How to measure in uence in social networks.- Developing a real-time tra c reporting and forecasting back-end system.- IoT Analytics Architectures: Challenges, solution proposals and future research directions.- Digital Enterprise and Technologies Structural Coupling, Strategy and Fractal Enterprise Modeling.- Systems-Thinking Heuristics for the Reconciliation of Methodologies for Design and Analysis for Information Systems Engineering.- An Ontology of IS Design Science Research Artefacts.- Evolution of Enterprise Architecture for Intelligent Digital Systems.- Human Factors in Information Systems Online peer support groups for behaviour change: Moderation requirements.- User-Experience in Business Intelligence - A Quality Construct and Model to Design Supportive BI Dashboards.- FINESSE: Fair Incentives forEnterprise Employees.- Explainable Recommendations in Intelligent Systems: Delivery Methods, Modalities and Risks.- Participation in Hackathons: A Multi-Methods View on Motivators, Demotivators and Citizen Participation.- Information Systems Development and Testing A systematic literature review of blockchain-enabled smart contracts: platforms, languages, consensus, applications and choice criteria.- Scriptless testing at the GUI level in an industrial setting.- Improving Performance and Scalability of Model-Driven generated Web applications: An experience report.- TesCaV: An Approach for Learning Model-based Testing and Coverage in Practice.- Machine Learning and Text Processing Automatic Classi cation Rules for Anomaly Detection in Time-series.- Text Embeddings for Retrieval from a Large Knowledge Base.- Predicting Unemployment with Machine Learning Based on Registry Data.- Anomaly detection on data streams - A LSTM's diary.- Process Mining, Discovery, and Simulation Discovering Business Process Simulation Models in the Presence of Multitasking.- TLKC-Privacy Model for Process Mining.- Incremental Discovery of Hierarchical Process Models.- Security and Privacy.- Ontology Evolution in the Context of Model-based Secure Software Engineering.- Blockchain-Based Personal Health Records for Patients' Empowerment.- COPri - a Core Ontology for Privacy Requirements Engineering.- Privacy Preserving Real-Time Video Stream Change Detection Based on the Orthogonal Tensor Decomposition Models.