Información de la conferencia

DATA 2023: International Conference on Data Science, Technology and Applications

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Día de Entrega:
2023-02-23
Fecha de Notificación:
2023-04-21
Fecha de conferencia:
2023-07-11
Ubicación:
Rome, Italy
Ediciones:
12
ICORE: C   Vistas: 18141   Seguidores: 5   Asistentes: 0

Solicitud de Artículos

DATA 2023 (International Conference on Data Science, Technology and Applications) is a ICORE C conference held in Rome, Italy on 2023-07-11. The paper submission deadline is 2023-02-23. Acceptance notifications are sent on 2023-04-21.

SCOPE The purpose of the International Conference on Data Science, Technology and Applications (DATA) is to bring together researchers, engineers and practitioners interested on databases, big data, data mining, data management, data security and other aspects of information systems and technology involving advanced applications of data. Papers describing advanced methodologies, prototypes, systems, tools and techniques and general survey papers indicating future directions are also encouraged. Papers describing original work are invited in any of the areas listed. Accepted papers, presented at the conference by one of the authors, will be published in the conference proceedings. Acceptance will be based on quality, relevance and originality. Both full research papers and work-in-progress are welcome. There will be both oral and poster sessions. Special sessions, dedicated to case-studies and commercial presentations, as well as demos or tutorials dedicated to technical/scientific topics are also envisaged: companies interested in presenting their products/methodologies or researchers interested in holding a tutorial, workshop or special session are invited to contact the conference secretariat or visit the conference website. CONFERENCE AREAS Each of these topic areas is expanded below but the sub-topics list is not exhaustive. Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas: 1. BUSINESS ANALYTICS 2. DATA SCIENCE 3. DATA MANAGEMENT AND QUALITY 4. BIG DATA 5. DATABASES AND DATA SECURITY AREA 1: BUSINESS ANALYTICS Business Intelligence Statistics Exploratory Data Analysis Text Analytics Web Analytics Change Detection Data Analytics Data Warehouse Management Decision Support Systems Dimensional Modelling Information Integration Information Retrieval Semi-Structured and Unstructured Data Data Governance AREA 2: DATA SCIENCE Data Fusion Pattern Recognition Predictive Modelling Support Vector Machines Data Science Data Mining Deep Learning Evolutionary Computing and Optimization Feature Selection Fuzzy Computing Hybrid Methods Neural Network Applications Process Mining Granular Computing AREA 3: DATA MANAGEMENT AND QUALITY Architectural Concepts Mobile Data Management Modeling and Managing Large Data Systems Open Data Organizational Concepts and Best Practices Smart Cities and Urban Data Analytics Transparency in Research Data City Data Management Data and Information Quality Data Management for Analytics Data Modeling and Visualization Data Structures and Data Management Algorithms Data Virtualization Industry 4.0 Management of Sensor Data Linked Data Semantic Web Technologies for Data Management AREA 4: BIG DATA Big Data Applications New Computational Models for Big Data New Data Standards Social Data Analytics Social Web Search and Mining Big Data as a Service Big Data Infrastructure Big Data Search and Mining Big Data Security, Privacy and Trust Cloud/Grid/Stream Computing for Big Data Data and Information Quality for Big Data Deep Learning and Big Data Information Visualization Edge Computing In-Network Data Processing Energy-Efficient Computing In-Memory Databases AREA 5: DATABASES AND DATA SECURITY Data Integrity WWW and Databases Data Privacy and Security Database Architecture and Performance Large Scale Databases Mobile Databases NoSQL Databases Object-Oriented Database Systems Open Source Databases Query Processing and Optimization
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