[Apologies for cross-posting]
Call for papers: Special Semantic Web Journal (SWJ) Issue on
Next to being one of the core research topics of AI since its beginnings, machine common sense has recently received new traction, mainly as a consequence of two factors: the recent surge of commonsense benchmarks, and the large success of neural language models on various AI tasks including commonsense question answering. In addition, many diverse structured and semi-structured sources of commonsense knowledge have been created, some of which are integrated in the Semantic Web. Given the gaps in current models and evaluation, such knowledge sources are leveraged to enhance these models and further improve performance on the benchmarks, as well as to enhance explainability and create novel evaluation challenges. Semantic Web sources thus hold the promise to advance the state-of-the-art research on commonsense knowledge and reasoning. This special issue at the Semantic Web Journal seeks original articles describing theoretical and practical methods and techniques focusing on open challenges with capturing commonsense knowledge, reasoning on tasks, and evaluating existing reasoning techniques in novel ways.
Topics relevant to this special issue include, but are not limited to, the following:
Representing and Storing Web of Data
Creation of new commonsense knowledge sources
Extraction of commonsense knowledge from text, images, or videos
Selecting commonsense knowledge from existing Semantic Web sources
Integration of existing commonsense knowledge sources
Integration of commonsense sources in the Linked Open Data cloud
Exploration of commonsense knowledge sources
Representation of commonsense knowledge
Domain ontologies of commonsense knowledge
Axiomatization of commonsense dimensions
Impact of commonsense knowledge on downstream tasks
Methods for including commonsense knowledge in downstream tasks
Using language models for commonsense reasoning
Probing for knowledge needs in downstream tasks
Evaluation metrics for machine common sense
Novel machine common sense tasks
Explainable commonsense reasoning
Multimodal commonsense reasoning
Domain-specific commonsense reasoning
Interactive elicitation or evaluation of commonsense knowledge
Identifying gaps in commonsense knowledge sources
Completion of commonsense knowledge sources
Submission deadline: 20th of October 2021. Papers submitted before the deadline will be reviewed upon receipt.
Submissions shall be made through the Semantic Web journal website at http://www.semantic-web-journal.net. Prospective authors must take notice of the submission guidelines posted at http://www.semantic-web-journal.net/authors.
We welcome five main types of submissions: (i) full research papers, (ii) reports on tools and systems, (iii) descriptions of ontologies, (iv) dataset descriptions, and (v) survey articles. The description of the submission types is posted at http://www.semantic-web-journal.net/authors#types. While there is no upper limit, paper length must be justified by content.
Note that you need to request an account on the website for submitting a paper. Please indicate in the cover letter that it is for the "Commonsense Knowledge and Reasoning" special issue. All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available online during the review process.
Also note that the Semantic Web journal is open access.
Finally please note that submissions must comply with the journal’s Open Science Data requirements, which are detailed in the corresponding blog post.
The guest editors can be reached at commons...@googlegroups.com .
Filip Ilievski, Information Sciences Institute, University of Southern California, CA, USA
Antoine Bosselut, Stanford University, CA, USA
Kenneth Forbus, Northwestern University, IL, USA
Simon Razniewski, Max Planck Institute for Informatics, Germany
Vered Shwartz, Allen Institute for AI and University of Washington, WA, USA
(to be expanded)
Maria Chang, IBM Almaden Research Center, CA, USA
Marieke van Erp, KNAW Humanities Cluster, The Netherlands
Bill Yuchen Lin, University of Southern California, CA, USA
Pavan Kapanipathi, IBM T J Watson Research Center, NY, USA
Alessandro Oltramari, Bosch Research, PA, USA
Ilaria Tiddi, Vrije Universiteit Amsterdam, The Netherlands
Hongming Zhang, The Hong Kong University of Science and Technology (HKUST), Hong Kong