Fourth Workshop on Cognitive Knowledge Acquisition and Applications
Acquire knowledge from text, reason in novel situations, and offer explanations in a Banking Question Answering and Reasoning shared task.
THANK YOU SPONSORS!
Following the success of the well-attended First, Second, and Third Cognitum workshops at IJCAI, we are excited to continue this workshop series at NAACL HLT 2018 in New Orleans, Louisiana. The Fourth Cognitum will focus on the integration of natural language processing and knowledge representation and reasoning, which has proved to be a particularly thorny problem. We solicit papers on this problem as well as participants in a shared task involving knowledge acquisition from text and answering and explaining the answers to natural language banking questions that require reasoning to answer.
KEYNOTE SPEAKER: Peter Clark, Allen Institute for Artificial Intelligence
To facilitate natural and fruitful interaction with humans, cognitive systems must be able to learn, reason, and communicate in natural language. Ultimately, this interaction aims to extend and enhance human cognition, not by having cognitive systems operate as subsidiary workers that solve problems for humans, but by having cognitive systems act as expert assistants able to collaborate with humans and provide them with help in a form compatible with how humans naturally process and understand information.
Knowledge acquisition is central to the design of such cognitive systems. Knowledge should be in a form that allows cognitive systems to understand natural language questions, perform reasoning to answer questions, and explain their reasoning. Unlike the significant body of work on mining the web for facts or answers to specific questions (such as NELL and IBM’s Watson Jeopardy! system), the workshop’s emphasis is on the acquisition of general knowledge that can be applied by cognitive systems in novel situations to perform reasoning. At the same time, acquired knowledge should be cognitive knowledge, which exhibits characteristics similar to human knowledge and allows systems to explain their reasoning.
We welcome ongoing and exciting preliminary work. Topics of interest include, but are not limited to:
- Integrating natural language processing with knowledge representation and reasoning.
- Acquiring cognitive knowledge (knowledge in a form that supports explanation to humans).
- Formal frameworks for acquiring cognitive knowledge.
- Deep learning for acquiring cognitive knowledge.
- Principled evaluation of acquired cognitive knowledge.
- Psychologically-guided design of the acquisition process.
- Considerations related to scalability and parallelization.
- Active choice among available learning data/resources.
- Representation languages for cognitive knowledge.
- Static versus temporal/causal cognitive knowledge.
- Interaction of acquisition with natural language processing, perception, and reasoning.
- Alternative acquisition methods (such as crowdsourcing).
- Acquisition from media other than text (such as video).
- Architecture and implementation of cognitive systems.
- Real-world applications that utilize cognitive knowledge.
March 2, 2018: Papers due
April 2, 2018: Notification of acceptance
April 16, 2018: Camera-ready papers due
June 5 or 6, 2018: Workshop in New Orleans, Louisiana, USA.
Submissions should follow the NAACL HLT 2018 style guidelines. Long paper submissions must follow the two-column format of ACL proceedings without exceeding eight (8) pages of content. Short paper submissions must also follow the two-column format of ACL proceedings, and must not exceed four (4) pages. References do not count against these limits. We strongly recommend the use of the official NAACL HLT 2018 style templates:
All submissions must be in PDF format.
Submission is electronic, using the Softconf START conference management system at:
Jason Alonso, Luminoso Technologies, Inc.
Ken Barker, IBM
Ernest Davis, New York University
James Fan, HelloVera.ai
Jonathan Gordon, USC Information Sciences Institute
Antonis Kakas, University of Cyprus
Zachary Kulis, Capital One
Margaret Mayer, Capital One
Rob Miller, University College London
J. William Murdock, IBM
Katerina Pastra, Cognitive Systems Research Institute
John Prager, IBM
Alessandra Russo, Imperial College London
Claudia Schulz, TU Darmstadt
Biplav Srivastava, IBM