A New Context-Based Similarity Measure for Categorical Data Using Information Theory-Reference-Cited by-同舟云学术

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A New Context-Based Similarity Measure for Categorical Data Using Information Theory

Published:2018 Issue: Volume: Page:114-125
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Nguyen Thanh-Phu,Ryoke Mina,Huynh Van-Nam

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-75429-1_10

Reference24 articles.

1. Cohen, J., Cohen, P.: Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. L. Erlbaum Associates, Hillsdale (1983)

2. Goodall, D.W.: A new similarity index based on probability. Biometrics 22(4), 882–907 (1966)

3. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);M Ring,2015

4. Lecture Notes in Computer Science;T-HT Nguyen,2016

5. Sokal, R.R., Sneath, P.H.A.: Principles of Numerical Taxonomy. W. H. Freeman, San Francisco (1961)

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An entropy-based weighted dissimilarity metric for numerical data clustering using the distribution of intra feature differences;Knowledge-Based Systems;2023-11

2. SEND: A novel dissimilarity metric using ensemble properties of the feature space for clustering numerical data;Information Sciences;2021-10

3. A New Context-Based Clustering Framework for Categorical Data;Lecture Notes in Computer Science;2018

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