Matching state-based sequences with rich temporal aspects
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Zheng, Aihua, Ma, Jixin, Tang, Jin and Luo, Bin (2012) Matching state-based sequences with rich temporal aspects. Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence. pp. 2463-2464.
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Official URL: http://www.aaai.org/ocs/index.php/AAAI/AAAI12/pape...
Abstract
A General Similarity Measurement (GSM), which takes into account of both non-temporal and rich temporal aspects including temporal order, temporal duration and temporal gap, is proposed for state-sequence matching. It is believed to be versatile enough to subsume representative existing measurements as its special cases.
Item Type: | Article |
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Additional Information: | [1] This paper was first presented at the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12) held from 22 - 26 July 2012 in Toronto, Canada. |
Uncontrolled Keywords: | General Similarity Measurement, (GSM), temporal order, temporal duration, temporal gap |
Subjects: | Q Science > QA Mathematics > QA76 Computer software |
Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science |
Related URLs: | |
Last Modified: | 04 Mar 2022 13:08 |
URI: | http://gala.gre.ac.uk/id/eprint/9700 |
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