Graph traversal methods for reasoning in large knowledge-based systems

Abhishek Sharma, Kenneth D Forbus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Commonsense reasoning at scale is a core problem for cognitive systems. In this paper, we discuss two ways in which heuristic graph traversal methods can be used to generate plausible inference chains. First, we discuss how Cyc's predicate-type hierarchy can be used to get reasonable answers to queries. Second, we explain how connection graph-based techniques can be used to identify script-like structures. Finally, we demonstrate through experiments that these methods lead to significant improvement in accuracy for both Q/A and script construction.

Original languageEnglish (US)
Title of host publicationProceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013
Pages1255-1261
Number of pages7
StatePublished - Dec 1 2013
Event27th AAAI Conference on Artificial Intelligence, AAAI 2013 - Bellevue, WA, United States
Duration: Jul 14 2013Jul 18 2013

Other

Other27th AAAI Conference on Artificial Intelligence, AAAI 2013
CountryUnited States
CityBellevue, WA
Period7/14/137/18/13

ASJC Scopus subject areas

  • Artificial Intelligence

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