The rapid growth of online available scientific, technical, and legal data such as patents, reports, articles, etc. has made the large-scale analysis and processing of such data a crucial task. Today, scientists, patent experts, inventors, and other information professionals (e.g., information scientists, lawyers, etc.) contribute to this data every day by publishing articles, writing technical reports, or patent applications.
It is a challenging task to process, analyze, and explore documents due to their length, the use of domain-specific vocabulary, and the complexity introduced by targeting various scientific fields and domains. Documents are semi-structured and cover unstructured textual parts as well as structured parts such as tables, mathematical formulas, diagrams, and domain-specific information such as chemical names, bio-sequences, etc.
Such kind of information brings complexity in processing such documents; however, data is the lifeblood of many applications, and its preservation, analysis, enrichment, and use are key for applications in several domains. In order to benefit from the scientific-technical knowledge present in such documents, e.g., for decision-making or for professional search and analytics, there is an urgent need for analyzing, enriching, and linking such data by employing state-of-the-art Semantic Web technologies and AI methods.
However, as they are heterogeneous and are written using domain-specific terminology applying the existing semantic technologies is not straightforward. To address the challenges mentioned above, Semantic Web Technologies, Natural Language Processing (NLP) techniques, Deep Neural Networks (DNN), and Large Language Models (LLMs) must be leveraged in order to provide efficient and effective solutions for creating easily accessible and machine-understandable knowledge.
The workshop accepts contributions in all topics related to semantic web technologies and deep learning focused (but not limited) to:
The submissions must be in English and adhere to the CEUR-WS one-column template (see Session 2: The New CEURART Style). The papers should be submitted as PDF files to EasyChair. The review process will be single-blind. Please be aware that at least one author per paper must be registered and attend the workshop to present the work and that ESWC is a 100% in person conference.
We will consider three different submission types:
Submissions should not exceed the indicated number of pages, including any diagrams and references.
Each submission will be reviewed by three independent reviewers on the basis of relevance for the workshop, novelty/originality, significance, technical quality and correctness, quality and clarity of presentation, quality of references and reproducibility.
The accepted papers will be available on the Workshop website. The proceedings will be published in a CEUR-WS volume and consequently indexed on Google Scholar, DBLP, and Scopus.
The registration to the workshop should be done by registering to TBD.
SemTech4STLD workshop will take place on May 26th or 27th, 2024.
The program will be published after the acceptance of the papers.