Similarity measure design on big data

Sanghyuk Lee; Yan Sun

doi:10.1007/978-94-007-6516-0_90

Similarity measure design on big data

Sanghyuk Lee^*, Yan Sun

^*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Abstract

Clustering algorithm in big data was designed, and its idea was based on defining similarity measure. Traditional similarity measure on overlapped data was illustrated, and application to non-overlapped data was carried out. Similarity measure on high dimension data was obtained through getting information from neighbor data. Its usefulness was proved, and verified by calculation of similarity for artificial data example.

Original language	English
Title of host publication	Future Information Communication Technology and Applications, ICFICE 2013
Pages	811-819
Number of pages	9
DOIs	https://doi.org/10.1007/978-94-007-6516-0_90
Publication status	Published - 2013
Event	2013 International Conference on Future Information and Communication Engineering, ICFICE 2013 - Shenyang, China Duration: 24 Jun 2013 → 26 Jun 2013

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	235 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	2013 International Conference on Future Information and Communication Engineering, ICFICE 2013
Country/Territory	China
City	Shenyang
Period	24/06/13 → 26/06/13

Keywords

Big data
High dimension data
Neighbor information
Similarity measure

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10.1007/978-94-007-6516-0_90

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title = "Similarity measure design on big data",

abstract = "Clustering algorithm in big data was designed, and its idea was based on defining similarity measure. Traditional similarity measure on overlapped data was illustrated, and application to non-overlapped data was carried out. Similarity measure on high dimension data was obtained through getting information from neighbor data. Its usefulness was proved, and verified by calculation of similarity for artificial data example.",

keywords = "Big data, High dimension data, Neighbor information, Similarity measure",

author = "Sanghyuk Lee and Yan Sun",

year = "2013",

doi = "10.1007/978-94-007-6516-0_90",

language = "English",

isbn = "9789400765153",

series = "Lecture Notes in Electrical Engineering",

pages = "811--819",

booktitle = "Future Information Communication Technology and Applications, ICFICE 2013",

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Lee, S & Sun, Y 2013, Similarity measure design on big data. in Future Information Communication Technology and Applications, ICFICE 2013. Lecture Notes in Electrical Engineering, vol. 235 LNEE, pp. 811-819, 2013 International Conference on Future Information and Communication Engineering, ICFICE 2013, Shenyang, China, 24/06/13. https://doi.org/10.1007/978-94-007-6516-0_90

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T1 - Similarity measure design on big data

AU - Lee, Sanghyuk

AU - Sun, Yan

PY - 2013

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N2 - Clustering algorithm in big data was designed, and its idea was based on defining similarity measure. Traditional similarity measure on overlapped data was illustrated, and application to non-overlapped data was carried out. Similarity measure on high dimension data was obtained through getting information from neighbor data. Its usefulness was proved, and verified by calculation of similarity for artificial data example.

AB - Clustering algorithm in big data was designed, and its idea was based on defining similarity measure. Traditional similarity measure on overlapped data was illustrated, and application to non-overlapped data was carried out. Similarity measure on high dimension data was obtained through getting information from neighbor data. Its usefulness was proved, and verified by calculation of similarity for artificial data example.

KW - Big data

KW - High dimension data

KW - Neighbor information

KW - Similarity measure

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U2 - 10.1007/978-94-007-6516-0_90

DO - 10.1007/978-94-007-6516-0_90

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SN - 9789400765153

T3 - Lecture Notes in Electrical Engineering

SP - 811

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BT - Future Information Communication Technology and Applications, ICFICE 2013

T2 - 2013 International Conference on Future Information and Communication Engineering, ICFICE 2013

Y2 - 24 June 2013 through 26 June 2013

ER -

Similarity measure design on big data

Abstract

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Keywords

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