Conférences  >  Informatique  >  Gestion des connaissances, Big Data Computing

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Réseaux de neurones et intelligence artificielle, apprentissage automatique,    Calcul scientifique et science des données

CARE College of Engineering, Tamil Nadu, India

In this digital era, Internet of Things [IoT], big data and computer networks are dedicated to provide new innovative contributions focused towards the development and deployment of wide range of intelligent and networked information systems. Smart IoT and big data platform allows the networked devices to communicate along with the core values of volume, variety and velocity which in turn leads to the integration of Big data and IoT with advanced machine learning and other advanced techniques. This International Conference on Computer networks, Big Data and IoT [ICCBI 2023] will provide an interdisciplinary platform to bring together scientists, researchers and academicians to present and exchange the ideas of the latest research works and results related to IoT, big data and computer networking topics.

Tél.: [9894161843];     Email.: icocbi.conf@gmail.com

Internet of Things AI and Machine Learning for the IoT Energy Efficiency and Sustainability in IoT Smart Sensing, Signal Processing and Analytics Human-Machine Interaction and IoT M2M/IoT Services over Distributed Networks Cloud/Fog/Edge-enabled Big Data Intelligence over IoT 6G-Enabled Internet of Things Security, Privacy, Intrusion Detection for the Internet of Things Big Data Multi-Modal Perceptual Big Data Analysis Intelligent Data Mining Machine Learning on Big Data Data Science and Scalable Computing Predictive Analytics and Simulation Big Data as a Service (BDaaS) Platform and Technologies Big Data System Reliability, Dependability, and Availability Knowledge Extraction, Discovery, and Analysis Security and Privacy-Aware Data Management Cloud Computing Cloud-centric Network Architectures Social and Mobile Cloud Applications Cloud Service Adaptation and Automation Fault Tolerance, Availability, and Reliability Distributed Ledger Technologies to Cloud Sustainable Cloud Computing Hybrid-clouds/Multi-clouds/Terminal-Edge-Cloud Integration Cloud Computing Virtualization

CIRM – Centre International de Rencontres Mathématiques

Calcul scientifique et science des données,    Réseaux sociaux et aspects sociaux des technologies de l'information

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Research data is essential to facilitate scientific progress, yet, many valuable datasets are hidden on web sites and small repositories or are hard to find due to insufficient metadata. Only a fraction of researchers pro-actively share dataset metadata through public portals, and curation of such metadata collections is costly. Unknown Data will provide means to automatically discover, extract, and publish metadata about research data that is hidden on the Web or in scholarly publications. Thus, the project’s goal is to improve findability and re-usability of research data by (a) improving metadata quality, in particular with respect to authority and use of existing datasets and (b) uncovering datasets that are not yet reflected in public data repositories and registries.

The event is sponsored by City University of Macau.

2024 the 2nd International Conference on Big Data will be held in Macau, China during January 10-12， 2024. This conference provides opportunities for the different areas delegates to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration. We hope that the conference results constituted significant contribution to the knowledge in these up-to-date scientific field.

Email.: saraxc17@163.com

Big Data Architecture and Systems; Deep Learning architecture, representations, unsupervised and supervised algorithms; Algorithmic, experimental, prototyping and implementation; Data Security and Management; Blockchain; Privacy and Security for Cloud and Big Data; Big Data Analysis and Computing; Big Data Mining and Analytics; Big Data Processing and Querying;

YOUNG-nd

The Organizing Committee is pleased to announce that 2024 The 7th International Conference on Software Engineering and Information Management (ICSIM 2024) will still be held in Fiji on January 23-25, 2024, which is sponsored by the University of Fiji.

Email.: emmaawang2019@sina.com

Software Agent Technology; Middleware Design Techniques; Reliability & Modeling Analysis; e-Government Engineering; Modeling with UML; Cost Modeling and Analysis; Information Management; Business strategy and information systems; Management Information Systems; Information systems planning and management; Adoption of information technology in organizations; Human factors in information systems;

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Graphs and knowledge bases have been around for many decades, and research outcomes have tremendously impacted areas like mathematics, artificial intelligence, and databases. However, despite being already coined by the scientific community, technological developments and astronomical data growth make knowledge graph management a fundamental topic nowadays in various computer science areas, supporting novel applications at the science (e.g., biomedicine) and industry (e.g., Google’s Knowledge Graph) level.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Many big data sets in various application domains have complex relationships, which can be modelled as graphs, consisting of entities and relationships between them. Consequently, graphs are extensively studied in both Mathematics and Computer science. In particular, planar graphs, which can be drawn without edge crossings in the plane, form a distinguished role in Graph Theory and Graph Algorithms. Many structural properties of planar graphs are investigated, in terms of excluded minors, low density, and small separators, which lead to efficient algorithms for planar graphs. Consequently, fundamental algorithms for planar graphs have been discovered. However, most real-world graphs, such as social networks and biological networks, are nonplanar. For example, the scale-free networks, which are used to model web graphs, social networks and biological networks, are globally sparse nonplanar graphs, with locally dense clusters and low diameters. To understand such real-world networks, we need to solve fundamental mathematical and algorithmic research questions on beyond-planar graphs, which generalize the notion of planar graphs, in terms of topological constraints or forbidden edge crossing patterns.

Théorie des graphes et combinatoire,    Calcul scientifique et science des données

The South Asia Institute of Science and Engineering

Warm welcome to the official website of 2024 the 10th International Conference on Information Management (ICIM2024). The conference will be held at the University of Cambridge, Cambridge, UK, from the 8th to the 10th of March, 2024.

Email.: brandon@saise.org

Information Management & Systems; Information Systems and Technology; E-Business Engineering and Management; Marketing Intelligence & Digital Marketing; Green marketing & Sustainable Business; Human Resources;

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Analyse,    Calcul infinitésimal, équations différentielles et intégrales

ICMS - International Centre for Mathematical Sciences

This workshop will gather researchers from the intersecting fields of inverse problems, uncertainty quantification, data analytics, machine learning, and related areas to discuss novel theory and new methods for big data challenges. A focused multifaceted research group gathered at one location is an excellent opportunity for established and early career researchers. The aim of this workshop is to foster a diverse, open, and friendly environment to advance this field, open new directions, and to stimulate new collaboration.

Calcul scientifique et science des données,    Mathématiques appliquées (en général)

The International Centre for Mathematical Sciences (ICMS)

This workshop will gather researchers from the intersecting fields of inverse problems, uncertainty quantification, data analytics, machine learning, and related areas to discuss novel theory and new methods for big data challenges. A focused multifaceted research group gathered at one location is an excellent opportunity for established and early career researchers. The aim of this workshop is to foster a diverse, open, and friendly environment to advance this field, open new directions, and to stimulate new collaboration. 

Department of Industrial Engineering, Faculty of Engineering, Chulalongkorn University

2024 9th International Conference on Big Data and Computing (ICBDC 2024) will be held during May 24-26, 2024 in Bangkok, Thailand . ICBDC 2024 is mainly organized by Department of Industrial Engineering, Faculty of Engineering, Chulalongkorn University.

Email.: Dunn@iact.net

Algorithmic, experimental, prototyping and implementation; Big Data Algorithms, Applications and Services; Big Data Mining and Analytics; Big Data Processing and Querying; Cloud and Big Data for Internet of Things (IoT); Computing, scheduling and resource management for sustainability; Government and Industrial Experiences for Cloud and Big Data; Green Computing and Networking Technologies for Cloud and Big Data;

YOUNG-nd

2024 The 7th International Conference on Artificial Intelligence and Big Data (ICAIBD 2024) will take place on May 24-27, 2024 in Chengdu, China. It is sponsored by Sichuan Province Computer Federation and technically assisted by many local and international universities.

Email.: emmaawang2019@sina.com

Intelligent information systems; Intelligent data mining and farming; Intelligent web-based business; AI and evolutionary algorithms; Big Data Analytics and Metrics; Cloud Computing Techniques for Big Data; Big Data Persistence and Preservation; Big Data Quality and Provenance Control; Big Data Economics; Neural networks and applications; Learning and adaptive sensor fusion; Management Issues of Social Network Big Data; Distributed, and Peer-to-peer Search; Machine learning based on Big Data;

The South Asia Institute of Science and Engineering

2024 8th International Conference on Information System and Data Mining (ICISDM 2024) will be held in Los Angeles, CA, USA during June 24-26, 2024.

Email.: brandon@saise.org

Information System, Engineering; Data Mining;

The South Asia Institute of Science and Engineering

The 7th International Conference on Big Data and Artificial Intelligence (BDAI2024) will be held at North China University of Technology, Beijing, China during July 5-7, 2024. The conference is co-sponsored by IEEE, Research Institute of Big Data Analytics at XJTLU, North China University of Technology, Beijing, China; Co-sponsored by Ocean University of China, China Agricultural University and South China University of Technology.

Ms. Ashley Liu;     Email.: brandon@saise.org

Big Data Models and Algorithms; Big Data Architectures; Big Data Management; Big Data Protection, Integrity and Privacy; Big Data Search and Mining; Artificial Intelligence;

The South Asia Institute of Science and Engineering

2024 8th High Performance Computing and Cluster Technologies Conference will be held in Beijing, China during July 5-7, 2024. HPCCT 2024 is co-sponsored by North China University of Technology, China and Xi’an Jiaotong-liverpool University, China. It provides a platform for academic exchange and showcasing achievements in the field of high performance computing and cluster technologies, delivering an academic feast for local and international experts and scholars.

Ms. Katharine Shui;     Email.: brandon@saise.org

Parallel and distributed system architectures; Languages and compilers for high performance computing; Embedded systems; Peer-to-peer computing; Grid and cluster computing; Web services and Internet computing; Cloud computing; Utility computing; Performance evaluation and measurement;

The South Asia Institute of Science and Engineering

We sincerely invite you to participate 2024 8th International Conference on Cloud and Big Data Computing. It will be held at Oxford Brookes University, Oxford, United Kingdom during August 15-17, 2024.

Ms. Vera Lee;     Email.: brandon@saise.org

Algorithmic, experimental, prototyping and implementation; Big Data Algorithms, Applications and Services; Big Data Mining and Analytics; Big Data Processing and Querying; Cloud computing and semantic web technologies; Cloud Computing Techniques for Big Data Analysis; Cloud Solution Design Patterns; Cloud for Enterprise Business Transformation;

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

The central topic of our Dagstuhl Seminar is the development, implementation, and evaluation of new AI technologies to support decision-making in management. A distinguishing feature is therefore innovative algorithms from the field of AI (e.g. explainable AI, generative AI, large language models, probabilistic ML, causal ML, etc.) that enable new insights in practice and beyond. This holds great potential for informing and improving decision-making.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Conversational Agents (CA) as frontends to Information Retrieval (IR) and Recommender Systems (RS) become more popular in everyday life, with a wider range of users and usages. The latest developments in Large Language Models (LLMs) will have tremendous consequences, especially for the workplace and education. In this Dagstuhl Perspectives Workshop, we want to focus on the evaluation of these conversational systems, as appropriate methods are still missing. The quality of these systems is limited in terms of personalization, veracity and correctness, bias, transparency, trustworthiness, and understandability. Thus, evaluation methods must address these shortcomings. Furthermore, user- and usage-oriented aspects should become a more prominent and integral component in evaluations, as the user population as well as the tasks these systems are used for become more heterogeneous. For this reason, the topic-centric view of relevance has to be extended to a broad range of facets which are important for the different usage scenarios. Therefore, suitable evaluation criteria have to be specified, which form the basis for defining appropriate measures. Most importantly, the range of evaluation methods must be revisited and extended, as popular methods like the Cranfield approach or crowdsourcing must be complemented by new evaluation methods and strategies specifically tailored to this new type of system.

Traitement automatique des langues, Linguistique informatique,    Mise en œuvre et applications de l'intelligence artificielle

International Academy of Computing Technology

2024 7th International Conference on Big Data and Machine Learning will be held in Xiamen, China during September 20-22, 2024. Machine Learning (ML) and Big Data Processing & Analytics (BDA) are both evolutionary fields of computing and the developments in these fields are complementing each other. The ever changing data landscape in modern digital world have resulted in newer ways of data processing frameworks in order to get meaningful insights which are unprecedented. ML based Big Data Processing has gained popularity and new developments are on the rise for efficient data processing. This field is witnessing unparalleled emergence of new methods and approaches for efficient data processing in order to discover interestingness for decision making. Thus, more and more ML based data processing approaches are being used for Big Data Processing. With the splurge data from different newer sources, heterogeneous nature of data, uncertain & unstructured data, the so called Big Data with all its characteristics (5 Vs) there is an ever increasing need to use approaches which aid in modelling and processing of these data, provide automated approach to data processing and so on. Thus the BDML conference series welcomes the scholars who are researching in this interesting & challenging domain of ML and Big Data Processing and provides an excellent international forum for sharing knowledge and results in theory, methodology and applications of Big Data and Machine Learning.

Email.: Dunn@iact.net

Big Data; Machine learning;

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Modern algorithms for data analysis require the use of advanced probabilistic methods to achieve desirable scalability and accuracy guarantees. At the same time, modern data-analysis tasks require the use of advanced statistics to handle challenges such as testing for multiple hypotheses or identifying dependencies among data points, such as in time series or graphs. Probabilistic methods are also at the core theoretical computer-science areas, such as sublinear algorithms and average-case analysis. To obtain efficient data-analysis algorithms, probabilistic methods require careful balancing of theoretical and practical aspects. This Dagstuhl Seminar brings together researchers interested in statistical and probabilistic methods to design and analyze scalable algorithms for discovering knowledge in large and rich datasets. We plan to cover the following topics, among others.

Statistique, Théorie des jeux,    Calcul scientifique et science des données

Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy / IAEA

Energie nucléaire,    Pédagogie de la science

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Data-sharing across domain and infrastructure boundaries is becoming more common, and significant work has been done in aligning many of the standard model describing the information and data being exchanged. In order to guarantee the scalability and practicality of data-sharing implementations, these standard models need to be aligned with the emerging technology architectures designed to support exchange networks at this scale. This workshop will look at how the standard metadata models for cross-domain use - including DDI-CDI and related models - and architectural approaches can best be used to leverage the strengths of both.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Through a series of Dagstuhl hosted workshops, and the CODATA-DDI collaboration, we have developed a framework for cross-domain interoperability, published by the EC-funded WorldFAIR project. This framework is being employed both within data intensive science and and between the scientific world and the world of official data, collected to inform policy making, including in relation to the Sustainable Development Goals and other components of the UN Agenda. The effective use and uptake of such a framework will require methodologies to evaluate implementations. This workshop will explore such approaches, building on current work for FAIR assessment, and the experience gained from implementation in a range of case studies, including those in WorldFAIR. The workshop will focus on improvements to evaluation metrics, and to the metadata exchange frameworks themselves.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

The vision of NFDI4DS is to support all steps of the complex and interdisciplinary research data lifecycle in Data Science and Artificial Intelligence. The overarching objective of NFDI4DS is the development, establishment, and sustainment of a national research data infrastructure for the Data Science and Artificial Intelligence community. The key idea is to work towards increasing the transparency, reproducibility and fairness of Data Science and Artificial Intelligence projects, by making all digital artifacts available, interlinking them, and offering innovative tools and services. Within this Dagstuhl Research Meeting, the NFDI4DS partners will reflect on their progress so far, and will work on their long-term strategy.

Réseaux de neurones et intelligence artificielle, apprentissage automatique,    Calcul scientifique et science des données