A method for k-means-like clustering of categorical data
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Despite recent efforts, the challenge in clustering categorical and mixed data in the context of big data still remains due to the lack of inherently meaningful measure of similarity between categorical objects and the high computational...
Saved in:
Main Authors: | Thu Hien Thi Nguyen, Duy Tai Dinh, Songsak Sriboonchitta, Van Nam Huynh |
---|---|
格式: | 雜誌 |
出版: |
2020
|
主題: | |
在線閱讀: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073982951&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/67757 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
ABC automatic blog categorizer using K-means algorithm
由: Agustin, Orlando Y., Jr., et al.
出版: (2009) -
Quantum approximate optimization and k-means algorithms for data clustering
由: Jirawat Saiphet, et al.
出版: (2022) -
Proximity-based k-partitions clustering with ranking for document categorization and analysis
由: Mei, Jian-Ping, et al.
出版: (2015) -
SCLOPE: An algorithm for clustering data streams of categorical attributes
由: ONG, Kok-Leong, et al.
出版: (2004) -
K-EVCLUS: Clustering large dissimilarity data in the belief function framework
由: Orakanya Kanjanatarakul, et al.
出版: (2018)