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Novel similarity measure for interval-valued data based on overlapping ratio

Kabir, Shaily; Wagner, Christian; Havens, Timothy C.; Anderson, Derek T.; Aickelin, Uwe

Authors

Shaily Kabir

Timothy C. Havens

Derek T. Anderson

Uwe Aickelin



Abstract

In computing the similarity of intervals, current similarity measures such as the commonly used Jaccard and Dice measures are at times not sensitive to changes in the width of intervals, producing equal similarities for substantially different pairs of intervals. To address this, we propose a new similarity measure that uses a bi-directional approach to determine interval similarity. For each direction, the overlapping ratio of the given interval in a pair with the other interval is used as a measure of uni-directional similarity. We show that the proposed measure satisfies all common properties of a similarity measure, while also being invariant in respect to multiplication of the interval endpoints and exhibiting linear growth in respect to linearly increasing overlap. Further, we compare the behavior of the proposed measure with the highly popular Jaccard and Dice similarity measures, highlighting that the proposed approach is more sensitive to changes in interval widths. Finally, we show that the proposed similarity is bounded by the Jaccard and the Dice similarity, thus providing a reliable alternative.

Citation

Kabir, S., Wagner, C., Havens, T. C., Anderson, D. T., & Aickelin, U. (2017). Novel similarity measure for interval-valued data based on overlapping ratio. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015623

Conference Name 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017)
Conference Location Naples, Italy
Start Date Jul 9, 2017
End Date Jul 12, 2017
Acceptance Date Mar 14, 2017
Online Publication Date Aug 24, 2017
Publication Date 2017
Deposit Date Apr 26, 2017
Publicly Available Date Mar 28, 2024
Journal Proceedings of the IEEE International Fuzzy Systems Conference
Electronic ISSN 1544-5615
Peer Reviewed Peer Reviewed
Pages 1-6
Series ISSN 1558-4739
Book Title 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
ISBN 978-1-5090-6035-1
DOI https://doi.org/10.1109/FUZZ-IEEE.2017.8015623
Public URL https://nottingham-repository.worktribe.com/output/878772
Publisher URL http://ieeexplore.ieee.org/document/8015623/
Additional Information Published in 2017 Proceedings of IEEE International Fuzzy Systems Conference. IEEE, 2017, isbn: 9781509060344. DOI: 10.1109/FUZZ-IEEE.2017.8015623

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