On clusterings-Reference-Cited by-同舟云学术

On clusterings

Published:2004-05 Issue:3 Volume:51 Page:497-515
ISSN:0004-5411
Container-title:Journal of the ACM
language:en
Short-container-title:J. ACM

Author:

Kannan Ravi¹,Vempala Santosh²,Vetta Adrian²

Affiliation:

1. Yale University, New Haven, Connecticut, CT

2. M.I.T., Cambridge, Massachusetts, MA

Abstract

We motivate and develop a natural bicriteria measure for assessing the quality of a clustering that avoids the drawbacks of existing measures. A simple recursive heuristic is shown to have poly-logarithmic worst-case guarantees under the new measure. The main result of the article is the analysis of a popular spectral algorithm. One variant of spectral clustering turns out to have effective worst-case guarantees; another finds a "good" clustering, if one exists.

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Hardware and Architecture,Information Systems,Control and Systems Engineering,Software

Link

https://dl.acm.org/doi/pdf/10.1145/990308.990313

Reference20 articles.

1. Spectral partitioning with multiple eigenvectors

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