Study on similarity measure for overlapped and non-overlapped data

Sanghyuk Lee; He Wei; T. O. Ting

doi:10.1109/ICIST.2013.6747498

Study on similarity measure for overlapped and non-overlapped data

Sanghyuk Lee
, He Wei
, T. O. Ting

Xi'an Jiaotong-Liverpool University

Research output: Contribution to conference › Paper › peer-review

3 Citations (Scopus)

Abstract

The analysis on similarity measure considering fuzzy sets (FSs) for the case of non-overlapped data is done in this work. Similarity measure on overlapped case was not adequate due to inconsistencies for non-overlapped data in terms of similarity calculation. Hence, another similarity was proposed and this is proven by neighbor data information. With artificial data, the rational calculation results are obtained. Additionally, similarity analysis on extension of FSs to intuitionistic fuzzy sets (IFSs) is carried out. IFSs contain uncertainty known as hesitance, which is contained in fuzzy membership function itself. In comparison of similarity measure to FSs and IFSs, the upper bound of IFSs similarity measure was also obtained.

Original language	English
Pages	48-53
Number of pages	6
DOIs	https://doi.org/10.1109/ICIST.2013.6747498
Publication status	Published - 2013
Event	2013 IEEE 3rd International Conference on Information Science and Technology, ICIST 2013 - Yangzhou, Jiangsu, China Duration: 23 Mar 2013 → 25 Mar 2013

Conference

Conference	2013 IEEE 3rd International Conference on Information Science and Technology, ICIST 2013
Country/Territory	China
City	Yangzhou, Jiangsu
Period	23/03/13 → 25/03/13

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10.1109/ICIST.2013.6747498

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abstract = "The analysis on similarity measure considering fuzzy sets (FSs) for the case of non-overlapped data is done in this work. Similarity measure on overlapped case was not adequate due to inconsistencies for non-overlapped data in terms of similarity calculation. Hence, another similarity was proposed and this is proven by neighbor data information. With artificial data, the rational calculation results are obtained. Additionally, similarity analysis on extension of FSs to intuitionistic fuzzy sets (IFSs) is carried out. IFSs contain uncertainty known as hesitance, which is contained in fuzzy membership function itself. In comparison of similarity measure to FSs and IFSs, the upper bound of IFSs similarity measure was also obtained.",

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AU - Ting, T. O.

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AB - The analysis on similarity measure considering fuzzy sets (FSs) for the case of non-overlapped data is done in this work. Similarity measure on overlapped case was not adequate due to inconsistencies for non-overlapped data in terms of similarity calculation. Hence, another similarity was proposed and this is proven by neighbor data information. With artificial data, the rational calculation results are obtained. Additionally, similarity analysis on extension of FSs to intuitionistic fuzzy sets (IFSs) is carried out. IFSs contain uncertainty known as hesitance, which is contained in fuzzy membership function itself. In comparison of similarity measure to FSs and IFSs, the upper bound of IFSs similarity measure was also obtained.

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T2 - 2013 IEEE 3rd International Conference on Information Science and Technology, ICIST 2013

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ER -

Study on similarity measure for overlapped and non-overlapped data

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