Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Efficient algorithms for fuzzy qualitative temporal reasoning

Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 and De Cock, M. 2009. Efficient algorithms for fuzzy qualitative temporal reasoning. IEEE Transactions on Fuzzy Systems 17 (4) , pp. 794-808. 10.1109/TFUZZ.2008.924333

Full text not available from this repository.

Abstract

Fuzzy qualitative temporal relations have been proposed to reason about events whose temporal boundaries are ill defined. Although the corresponding reasoning tasks are in the same complexity class as their crisp counterparts, in practice, the scalability of fuzzy temporal reasoners may be insufficient for applications that require a high expressivity and deal with a large number of events. On the other hand, transitivity rules can be used to make sound but incomplete inferences in polynomial time, utilizing a variant of Allen's path-consistency algorithm. The aim of this paper is to investigate how this polynomial time algorithm can be improved without altering its time complexity. To this end, we establish a characterization of 2-consistency of fuzzy temporal relations and provide transitivity rules that are significantly stronger than those resulting from straightforwardly generalizing transitivity rules for crisp temporal relations. We furthermore provide experimental evidence for the effectiveness of our improved algorithm.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Uncontrolled Keywords: Fuzzy Relations ; Fuzzy relations ; Qualitative Reasoning ; Temporal Reasoning ; Qualitative reasoning ; Temporal reasoning
Publisher: Institute of Electrical and Electronics Engineers
ISSN: 1063-6706
Last Modified: 20 Oct 2022 09:24
URI: https://orca.cardiff.ac.uk/id/eprint/31828

Citation Data

Cited 5 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item