Consensus Clustering Based on a New Probabilistic Rand Index with Application to Subtopic Retrieval

被引：47

作者：

Carpineto, Claudio ^{[1
]}

Romano, Giovanni ^{[1
]}

机构：

[1] Fdn Ugo Bordoni, I-00161 Rome, Italy

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2012年 / 34卷 / 12期

关键词：

Consensus clustering; Rand index; probabilistic Rand index; search results clustering; subtopic retrieval;

D O I：

10.1109/TPAMI.2012.80

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We introduce a probabilistic version of the well-known Rand Index (RI) for measuring the similarity between two partitions, called Probabilistic Rand Index (PRI), in which agreements and disagreements at the object-pair level are weighted according to the probability of their occurring by chance. We then cast consensus clustering as an optimization problem of the PRI value between a target partition and a set of given partitions, experimenting with a simple and very efficient stochastic optimization algorithm. Remarkable performance gains over input partitions as well as over existing related methods are demonstrated through a range of applications, including a new use of consensus clustering to improve subtopic retrieval.

引用

页码：2315 / 2326

页数：12