Konferenzen  >  Informatik  >  Informations & Wissensmanagement, Big Data Computing

5th International Conference on Big Data, IOT & NLP (BINLP 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Big Data, IoT and NLP. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Big Data, Internet of Things and NLP.

Tel.: [9677141480];     Email: binlp@myyahoo.com

• Big Data & Business Intelligence, • Information Extraction, Retrieval, • Semantic Processing & NLP,

Internet der Dinge (IoT) und Sensornetze,    Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen

York College, City University of New York

We are pleased to warmly invite you to the International Conference On Business, Management, Economics, and Information Systems - 2025 (ICBMEIS-2025), organized by the Department of Business and Economics, York College, City University of New York (CUNY), Jamaica, New York, United States. ICBMEIS - 2025 is scheduled for October 25-26, 2025, at the Department of Business and Economics. ICBMEIS - 2025‎ is dedicated to fostering the exchange of knowledge, innovative ideas, and discussions on the latest advancements in the fields of Business, Management, Economics, and Information Systems. This conference will provide a valuable platform for esteemed academicians, scholars, and researchers to connect, collaborate, and interact with peers from both national and international arenas.

Conference Secretariat;     Email: icbm@york.cuny.edu

Business, Management, Entrepreneurship, Supply Chain Management, Operations Management, Human Resource Management, Marketing, Information Systems, Economics, Data Analytics, Engineering & Technology, Accounting and Finance, Sustainability, Aviation Management

Wirtschaftswissenschaft, Unternehmen und Marketing,    Berufliche Laufbahn und Management

United Arab Emirates University, ADA University, Politecnico di Torino, George Washington University

The AICT2025 will offer keynotes, tutorials and research presentations. Submitted papers are expected to cover state-of-the-art technologies, theoretical concepts, standards, products implementation, ongoing research projects as well as application issues of ICT. In previous AICT’s hundreds of participants from more than 70 counties have participated.

Email: aict@aict.info

entwickler.de Akademie | Software & Support Media GmbH

Die Teilnehmenden lernen hier Wege zur Realisierung dynamischer Cloud-Native-Architekturen, Container Application Design, Logging/Monitoring/Alerting, Container Native Storage und Möglichkeiten zur UI-Integration. Ebenso werden typische Konzepte aktueller Container-Manager aufgezeigt und vermittelt, wie sich damit für größere Webanwendungen gängige Qualitätsanforderungen realisieren lassen. Zusätzlich werden bekannte Cloud-Anbieter klassifiziert, Möglichkeiten zur Automatisierung aufgezeigt, Ansätze der Softwareentwicklung und des Application Lifecycle besprochen.

entwickler.de Akademie;     Email: info@entwickler-akademie.de

Infrastruktur, Container und Cloud Native, iSAQB, Schulung, Trainer, Fortbildung, Weiterbildung, Software-Architecture, Camp, Advanced, Credits, loud-Native-Architekturen, Container Application Design, Logging/Monitoring/Alerting, Container Native Storage, UI-Integration

Edge/Cloud-Computing,    Eingebettete Systeme, RFIDs

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

More and more, we find that the provenance of data is a key missing ingredient in the information set made available to us. Provenance - the origination and intention of data as collected - provides significant challenges for modern networks. While standards exist for describing data and its analysis - and even for parts of the provenance chain - there is no standard mechanism for tying together all relevant information across the series of steps which fully describe the origination of data. This workshop explores how the many contextualising factors needed to support responsible and accurate data reuse can be described, allowing for the needed chaining of provenance steps.

Université Sultane Moulay Slimane, Laboratoire d'Ingénierie des Procédés, Informatique et Mathématiques

ICMICSA'25 is a peer-reviewed hybrid conference where researchers can present their paper in front of experts in different disciplines and backgrounds either in online or in-person mode during the conference dates. The conference will provide a platform to disseminate knowledge and results in theory, methodology and techniques in engineering and sciences and it will covers a broad spectrum of trending topics.

Comité d'organisation;     Email: icmicsa@usms.ma

AI, Machine Learning & Data Processing, Deep Learning, Natural Language Processing, Pattern Recognition, Computer Vision, Data Mining, Data Science, Big Data Analytics, Systems & Infrastructure, Cloud and Edge Computing, High­ Performance Computing, Information Systems Software Engineering, Emerging Technologies, IoT and Sensor Networks, Robotics and Automation, Human–Computer Interaction, Bioinformatics, Cyber Security

Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen,    Allgemeine und fachübergreifende Veranstaltugen in Informatik

SEIT Lab, Department of Computer Science, University of Cyprus

The annual IEEE International Conference on Knowledge Graph (ICKG) provides a premier

international forum for presentation of original research results in knowledge discovery and

graph learning, discussion of opportunities and challenges, as well as exchange and

dissemination of innovative, practical development experiences. The conference covers all

aspects of knowledge discovery from data, with a strong focus on graph learning and

knowledge graph, including algorithms, software, platforms. ICKG 2025 intends to draw

researchers and application developers from a wide range of areas such as knowledge

engineering, representation learning, big data analytics, statistics, machine learning, pattern

recognition, data mining, knowledge visualization, high performance computing, and World

Wide Web etc. By promoting novel, high quality research findings, and innovative solutions to

address challenges in handling all aspects of learning from data with dependency relationship.

All accepted papers will be published in the conference proceedings by the IEEE Computer

Society. Awards, including Best Paper, Best Paper Runner up, Best Student Paper, Best Student

Paper Runner up, will be conferred at the conference, with a check and a certificate for each

award. The conference also features a survey track to accept survey papers reviewing recent

studies in all aspects of knowledge discovery and graph learning. At least five high quality

papers will be invited for a special issue of the Knowledge and Information Systems Journal,

in an expanded and revised form. In addition, at least eight quality papers will be invited for a

special issue of Data Intelligence Journal in an expanded and revised form with at least 30%

difference.

Tel.: [00357722892693];     Email: george@ucy.ac.cy

• Foundations, algorithms, models, and theory of knowledge discovery and graph learning • Knowledge engineering with big data. • Machine learning, data mining, and statistical methods for data science and engineering. • Acquisition, representation and evolution of fragmented knowledge. • Fragmented knowledge modeling and online learning. • Knowledge graphs and knowledge maps. • Graph learning security, privacy, fairness, and trust. • Interpretation, rule, and relationship discovery in graph learning. • Geospatial and temporal knowledge discovery and graph learning. • Ontologies and reasoning. • Topology and fusion on fragmented knowledge. • Visualization, personalization, and recommendation of Knowledge Graph navigation and interaction. • Knowledge Graph systems and platforms, and their efficiency, scalability, and privacy. • Applications and services of knowledge discovery and graph learning in all domains including web, medicine, education, healthcare, and business. • Big knowledge systems and applications. • Crowdsourcing, deep learning and edge computing for graph mining. • Large language models and applications • Open source platforms and systems supporting knowledge and graph learning. • Datasets and benchmarks for graphs • Neurosymbolic & Hybrid AI systems • Graph Retrieval Augmented Generation

IADIS

The IADIS Information Systems Conference (IS 2026) aims to provide a forum for the discussion of IS taking a socio-technological perspective. It aims to address the issues related to design, development and use of IS in organisations from a socio-technological perspective, as well as to discuss IS professional practice, research and teaching.

Conference Secretariat;     Email: secretariat@is-conf.org

IS in Practice, Technology Infrastructures and Organisational Processes; IS Professional Issues; IS Learning and Teaching; IS Design, Development and Management Issues and Methodologies; and IS Research

KAOUN International

Accelerated by GITEX GLOBAL, the world’s largest tech and startup show, GITEX ASIA x AI EVERYTHING SINGAPORE unites global AI pioneers, digital infrastructure leaders, frontier startups, strategic investors and policymakers to accelerate transformation across every major sector. From public-private collaboration to enterprise adoption, the show delivers real outcomes, deep partnerships, and future-defining breakthroughs - live from Singapore, Asia's capital of Innovation.

GITEX ASIA MARKETING;     Tel.: [0555732365];     Email: marketing@gitexasia.com

Informationssicherheit und Datenschutz,    Datenbanktechlologie, Suchmaschinen und Data-Mining

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Autonomous AI agents, empowered by recent advances in Large Language Models (LLMs) and generative AI, are rapidly changing how we interact with, structure, and reason about information. These "agentic" systems go beyond static analysis – they act: interpreting their environment, interacting with humans and other agents, and autonomously executing tasks. This evolution opens new doors for knowledge engineering, especially in the context of increasingly complex, dynamic, and human-centric information spaces. While traditional knowledge engineering emphasized structured symbolic representations (e.g., ontologies, knowledge graphs) and formal reasoning, modern generative agents leverage machine-learned representations and natural language interfaces to emulate intelligent behavior. However, this comes with new challenges: How can we ensure such agents are interpretable, controllable, and aligned with human expectations? What is the role of hybrid systems that combine symbolic reasoning and statistical learning? This meeting will explore agentic AI as a foundation for the next generation of knowledge engineering systems – those that not only understand and transform data, but can also autonomously interact, reason, and collaborate.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

The aim of this Dagstuhl Seminar is to bring together researchers from different subfields of computer science that study or use techniques in knowledge compilation.

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Explainable AI; Knowledge Representation; Neuro-Symbolic AI; Machine Learning