Ontology Summit 2024
(from: https://ontologforum.com/index.php/OntologySummit2024)
Hybrid Neuro-Symbolic Techniques for and with Ontologies and Knowledge Graphs
The Ontology Summit is an annual series of events that involves the ontology community and communities related to each year’s theme chosen for the summit. The Ontology Summit was started by Ontolog and NIST, and the program has been co-organized by Ontolog and NIST along with the co-sponsorship of other organizations that are supportive of the Summit goals and objectives.
As part of Ontolog’s general advocacy to bring ontology science and related engineering into the mainstream, we endeavor to facilitate discussion and knowledge sharing amongst stakeholders and interested parties relevant to the use of ontologies. The results will be synthesized and summarized in the form of the Ontology Summit 2024 Communiqué, with expanded supporting material provided on the web and in journal articles.
Description
The summit will survey current techniques that combine neural network machine learning with symbolic methods, especially methods based on ontologies and knowledge graphs.
Ontologies are representations of a knowledge domain. They define the concepts, relationships, properties, axioms and rules within that domain, providing a framework that enables a deep understanding of that subject area. Knowledge graphs are structured representations of semantic knowledge that are stored in a graph. Ontologies and knowledge graphs are used to enable machine reasoning and semantic understanding, allowing a system to draw inferences and to derive new information and relationships between entities.
Neural network and other machine learning models, such as LLMs, are trained on large corpora, learning the patterns and connections between words and images. Hence, although their “knowledge base” is broad, it is also sometimes incorrect and/or biased, and doesn’t explicitly understand the semantics or relationships in that content.
Consequently, neural network and traditional AI techniques are complementary. The Fall Series of the summit explored the similarities and distinctions between ontologies and LLMs, as well as how they can be used together. The Main Summit Series will examine the more general topic of neuro-symbolic techniques, especially how one can leverage the complementary benefits of neural networks and of ontologies and knowledge graphs.
Main Series Chair Ken Baclawski
- Track A. Foundations and Architectures
- Track B. Large Language Models, Ontologies and Knowedge Graphs
- Track C. Applications
- Track D. Risks and Ethics
Schedule
- 21 February 2024 Kickoff/Overview
- 28 February 2024 Track A Session 1
- Gary Marcus
- John Sowa Without Ontology, LLMs are clueless
- 6 March 2024 Track B Session 1 Hamed Babaei Giglou LLMs4OL: Large Language Models for Ontology Learning
- 13 March 2024 Track B Session 2 Fabian Neuhaus Ontologies in the era of large language models – a perspective
- 20 March 2024 Track A Session 2 Till Mossakowski Modular design patterns for neural-symbolic integration: refinement and combination
- 27 March 2024 Track A Session 3 Amit Sheth
- 3 April 2024 First Synthesis
- 10 April 2024 Track C Applications Session 1 Finance
- 17 April 2024 Track C Applications Session 2 Manufacturing
- 24 April 2024 Track C Applications Session 3 Healthcare
- 1 May 2024 Track D Session 1 Risk Panel
- 8 May 2024 Track D Session 2 Ethics Panel
- 15 May 2024 Second Synthesis
- 22 May 2024 Communiqué