KGSum2022: International Workshop on Knowledge Graph Summarization The 21st International Semantic Web Conference Hangzhou, China, October 23-27, 2022 |
Conference website | https://kgsum.github.io/ |
Submission link | https://easychair.org/conferences/?conf=kgsum2022 |
Abstract registration deadline | July 21, 2022 |
Submission deadline | July 21, 2022 |
There is a growing interest in generating summaries from the facts contained in a Knowledge Graph. Condensing relevant information into a few statistical data, sentences, paragraphs, or triplets is an emerging problem that remains to be solved as knowledge graphs increase complexity and expand in size and domains.
Knowledge Graph Summarization (KGSum) aims at producing concise but informative descriptions of the content of a knowledge graph that help users to efficiently access and distill valuable information from it. Conversational systems, question-answering services or any other method leveraging the narrative content around the entities in a knowledge graph will benefit from these techniques.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. All submissions must be in English and follow the CEURART format. Proceedings of the workshop will be publicly available under CC-by 4.0 license.
The following paper categories are welcome:
- Research papers (8-12 pages)
- In Use and Experience papers (8-12 pages)
- Short research papers (4-6 pages)
- System/demo/Position papers (4-6 pages)
List of Topics
We welcome submissions from multiple areas such as Semantic Web, Linked Data, Natural Language Processing (NLP), Entity Linking (EL), Knowledge Representation and Reasoning (KRR), and other related fields that address the following topics (but not limited to):
- Methods to summarize KGs
- Research work and initiatives related to verbalizing facts expressed through subject-predicate-object triplets
- Automatic generation of textual summaries as a way to measure the quality of KGs
- Integration between Language Models and KGs
- KGs features that affect summaries
- Special features/metadata from KGs to generate coherent multi-sentence summaries
- Extensions to current KGs formalisms to better support summaries
- Benefits of incorporating automatic generation of textual summaries on KGs
- Scope and Impact of KG summaries
- Use cases and applications for KGs summaries
- Generating adaptive summaries from KGs so they suit the needs of the different agents consuming it.
- Importance/role of KGs in the generation of summaries that express complex ideas
- How KGs in conjunction with textual summaries can be used to improve QA systems
Committees
Program Committee
- Gaetano Rossiello, IBM Research
- Soto Montalvo, Universidad Rey Juan Carlos
- Emilio Monti, Amazon
- Pasquale Lisena, Eurecom
- Pablo Calleja Ibañez, Universidad Politécnica de Madrid
- Hegler Tissot, Drexel University
- Patricia Martín Chozas, Universidad Politécnica de Madrid
- Boris Villazon-Terrazas, Tinámica
Organizing committee
- Carlos Badenes-Olmedo, Universidad Politécnica de Madrid
- Jose Luis Redondo-García, Amazon Alexa
- Nandana Mihindukulasooriya, IBM Research AI
- Maribel Acosta, Ruhr University Bochum
Publication
KGSum2022 proceedings will be published in CEUR.
Reviewing policy: Submissions will be evaluated by members of the Program Committee. The workshop follows a double-blind review process, where the identity of both authors and reviewers are concealed. Submitted papers must be anonymized.
Contact
More info in our website: https://kgsum.github.io