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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.

The 8th International Conference on Algorithmic Decision Theory (ADT 2024) focuses on algorithmic decision theory broadly defined, seeking to bring together researchers and practitioners coming from diverse areas of Computer Science, Economics, and Operations Research in order to improve the theory and practice of modern decision support.

Gestion des connaissances, Big Data Computing,    Soft computing, algorithmes évolutionnaires, domaine des métaheuristiques, logique floue

The 15th Multidisciplinary Workshop on Advances in Preference Handling (M-PREF 2024) addresses all computational aspects of preference handling. This includes methods for the elicitation, learning, modeling, representation, aggregation, and management of preferences and for reasoning about preferences. The workshop studies the usage of preferences in computational tasks from decision making, database querying, web search, personalized human-computer interaction, personalized recommender systems, e-commerce, multi-agent systems, game theory, social choice, combinatorial optimization, planning and robotics, automated problem solving, perception and natural language understanding and other computational tasks involving choices. The workshop seeks to improve the overall understanding of and best methodologies for preferences in order to realize their benefits in the multiplicity of tasks for which they are used. Another important goal is to provide cross-fertilization between the numerous sub-fields that work with preferences.

Gestion des connaissances, Big Data Computing,    Soft computing, algorithmes évolutionnaires, domaine des métaheuristiques, logique floue

Henry Stewart Events

Chaired by Jarrod Gingras, Managing Director & Analyst at Real Story Group, Creative Tech New York, a one-day event that will explore the intersection of technology and creativity in today's content supply chain. Through panel discussions and keynote sessions. Covering topics such as automation at scale, sophisticated workflows, global omnichannel management, VR and AR advancements, AI-driven creative processes, innovative AdTech and MarTech trends, and storytelling in the digital era. As enterprises strive to balance personalized experiences with the demand for content, this event provides valuable insights into navigating the challenges while preserving creativity.

Email.: JennyM@henrystewart.co.uk

creative tech, creative technology, adtech, advertising technology, martech, marketing technology, creative process, omnichannel, Digital Creativity, Creative Innovation, Technology Integration, Digital Media, Interactive Design, Digital Art, Creative Coding, Virtual Reality (VR), Augmented Reality (AR), User Experience (UX) Design, Interactive Installations, Multimedia Production, Digital Advertising, Creative Programming, Immersive Experiences, Digital Storytelling, Creative Solutions, Innovative Design, Media Technology, Artificial Intelligence (AI) in Creativity, Digital Marketing Creativity, Tech-Enhanced Creativity, Media Production Technology, Creative Applications of Technology, Emerging Creative Technologies, omnichannel variants, AI driven processes, AI driven creative processes

Sciences économiques, Entreprise et Marketing,    e-Business, Administration électronique, Logiciel en tant que service

The TREC Conference series is co-sponsored by the NIST Information Technology Laboratory's (ITL) Retrieval Group of the Information Access Division (IAD)

The Text Retrieval Conference (TREC) workshop series encourages research in information retrieval and related applications by providing a large test collection, uniform scoring procedures, and a forum for organizations interested in comparing their results.

Institute for Artificial Intelligence, Peking University

The Ninth International Conference on Data Mining and Big Data ([*ACRONYM*]) serves as an international forum for researchers and practitioners to exchange latest advantages in theories, algorithms, models, and applications of data mining and big data as well as artificial intelligence techniques. Data mining refers to the activity of going through big data sets to look for relevant or pertinent information. Big data contains huge amount of data and information and is worth researching in depth. [*ACRONYM*] is the ninth event after the preceding Sanya, Beijing, Guangzhou, Belgrade, Chiang Mai, Shanghai, Fukuoka and Bali events where more than hundreds of delegates from all over the world to attend and share their latest achievements, innovative ideas, marvelous designs and excel implementations.

Email.: dmbd2024@iasei.org

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Semirings are fundamental algebraic structures that in recent times have found a number of applications to computer science, especially in the areas of databases and automata. On the side of databases, commercial query languages, such as SQL, use bag semantics, instead of set semantics, to evaluate relational database queries, which means that the semiring of the natural numbers is used to annotate tuples in the input and output relations. More generally, the annotations can be values in some fixed semiring; this gives a common generalization of both set semantics and bag semantics of database queries, and also makes it possible to model other situations in which one is interested, e.g., in the probability or the reliability of an answer. Furthermore, semirings of polynomials have been successfully used to carry out a rigorous study of provenance in databases. On the side of automata, semirings are used to define weighted automata, which are nondeterministic finite automata augmented with values from a semiring as weights on the transitions. These weights may model, e.g., the cost involved when executing a transition, the amount of resources or time needed for this, or the probability or reliability of its successful execution. Weighted automata have found numerous applications to natural language processing, speech recognition, and algorithms for digital image compression. These applications have inspired numerous investigations in the logic-in-computer-science community.

Théorie de l'information, fondations de l'informatique,    Génie logiciel

International Academy of Computing Technology

2025 9th International Conference on Digital Signal Processing (ICDSP 2025) will be held in Chengdu, China during February 21-23, 2025. It is Co-sponsored by Southwest Jiaotong University and Xihua University, China, and technically supported by many universities and institutions.

Email.: Dunn@iact.net

MACHINE LEARNING AND STATISTICAL SIGNAL PROCESSING; DIGITAL AND MULTIRATE SIGNAL PROCESSING; DESIGN AND IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS; SPEECH AND LANGUAGE PROCESSING; AUDIO AND ACOUSTIC SIGNAL PROCESSING;

USENIX Association

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Process mining and visual analytics are separate disciplines with the common goal of helping humans gain insight into and extract knowledge about relevant phenomena from complex data. Process mining (PM) is a rapidly growing discipline blending machine learning and data mining concepts with ideas taken from the field of business process management (BPM). It utilizes event data recorded by IT systems that support business process execution for a variety of tasks, from the automated discovery of graphical process models to operational support. Visual Analytics (VA) is a multidisciplinary approach that combines interactive, visual, and analytical methods to make complex phenomena more comprehensible, facilitate new insights, and enable knowledge discovery. VA research happens at the intersection of data mining and knowledge discovery, information visualization, human-computer interaction, and cognitive science.

Society for Industrial and Applied Mathematics (SIAM)

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Data structures are the science of organizing and accessing data, and their study is a core part of computer science. They underpin our computing infrastructure with efficiency being of critical importance. As the computing landscape changes with more demanding tasks arising, data structure research remains vibrant, with two aspects coming particularly in focus: scalability and adaptivity. Scalability means that data structures remain efficient as data sets increase, become more dynamic, and become more distributed. Adaptivity implies taking advantage of modern hardware, such as multicore computation or memory hierarchies, as well specific structure and biases in the operations performed. One seeks to create structures that maximally take advantage of such architectural and distributional details without any foreknowledge of them. General limits of adaptivity have long posed deep theoretical questions, which continue to inspire research. This Dagstuhl Seminar is part of a successful series begun in 1991. The series has contributed to shaping trends in data structures research.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

This summer school is an intensive course on software techniques for data management and database management. Topics include database command translation and query optimization, query execution and indexing, row- and column-oriented storage structures and algorithms, optimistic and pessimistic concurrency control, logging and recovery, replication and high availability, scalability and cloud computing, and more. The goal of lectures and presentations is to understand classic techniques and to link them to industrial reality and to research opportunities. The target audience are recent MS graduates who have already taken 2-3 courses covering data management software and who are embarking on a career in industrial development or in academic research in related topics.

Evènements pour étudiants en informatique,    Gestion des connaissances, Big Data Computing

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

The Autumn School for Information Retrieval and Information Foraging (ASIRF) focuses on recent developments in Information Retrieval and Information-Seeking behavior and their applications. Information Retrieval deals with searching in huge amounts of unstructured data. In many professional fields of work and everyday life, access to text data via search engines is one of the most important forms of access to knowledge. Information Foraging aims to model the entire process from the awareness of an information problem through selecting appropriate information sources to the actual search.

Students and lecturers will live together for a week at Schloss Dagstuhl, which guarantees the school's traditionally highly communicative and interactive atmosphere. The intended audience of ASIRF are doctoral students and young researchers working in Information Retrieval, Information Foraging, or using concepts or methods from these fields in their research

Evènements pour étudiants en informatique,    Gestion des connaissances, Big Data Computing

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Retrieval-augmented generation (RAG) has proven effective in conditioning the output of large language models (LLMs) on relevant documents and for grounding LLM-generated statements, this way combatting the so-called confabulation or hallucination problem. Basically, RAG combines (1) a retrieval phase, where a search system identifies relevant documents for a user prompt, and (2) a generation phase, where an LLM synthesizes a tailored answer, probably linking to the retrieved sources.