Clustering approaches for high‐dimensional databases: A review-Reference-Cited by-同舟云学术

Clustering approaches for high‐dimensional databases: A review

Published:2019-01-23 Issue:3 Volume:9 Page:
ISSN:1942-4787
Container-title:WIREs Data Mining and Knowledge Discovery
language:en
Short-container-title:WIREs Data Mining Knowl Discov

Author:

Mittal Mamta¹,Goyal Lalit M.²,Hemanth Duraisamy Jude³,Sethi Jasleen K.⁴

Affiliation:

1. Department of Computer Science and Engineering G.B. Pant Government Engineering College New Delhi India

2. Department of Computer Engineering J.C. Bose University of Science & Technology, YMCA Faridabad India

3. Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences Coimbatore India

4. Department of Computer Science and Engineering, University School of Information, Communication and Technology (USICT) Guru Gobind Singh Indraprastha University (GGSIPU) New Delhi India

Publisher

Wiley

Subject

General Computer Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/widm.1300

Reference84 articles.

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4. Agrawal R. &Srikant R.(1994). Fast algorithms for mining association rules.Proceedings of the 20th VLDB Conference(pp. 487–499).

5. Ankerst M. Breuing M. M. Kriegel H.‐P. &Sander J.(1999). OPTICS: Ordering points to identify the clustering structure.Proceedings of the ACM SIGMOD International Conference on Management of Data(pp. 49–60).

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