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Plausible reasoning based on qualitative entity embeddings

Schockaert, Steven and Jameel, Shoaib 2016. Plausible reasoning based on qualitative entity embeddings. Presented at: 25th International Joint Conference on Artificial Intelligence, New York, USA, 9-15 July 2016.

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Abstract

Formalizing and automating aspects of human plausible reasoning is an important challenge for the field of artificial intelligence. Practical advances, however, are hampered by the fact that most forms of plausible reasoning rely on background knowledge that is often not available in a structured form. In this paper, we first discuss how an important class of background knowledge can be induced from vector space representations that have been learned from (mostly) unstructured data. Subsequently, we advocate the use of qualitative abstractions of these vector spaces, as they are easier to obtain and manipulate, among others, while still supporting various forms of plausible reasoning.

Item Type: Conference or Workshop Item (Paper)
Date Type: Completion
Status: Unpublished
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Funders: ERC
Related URLs:
Date of First Compliant Deposit: 25 April 2016
Date of Acceptance: 27 March 2016
Last Modified: 12 Jun 2019 03:02
URI: http://orca.cf.ac.uk/id/eprint/89927

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