模糊聚类和分类算法KMART和FCM的质量和性能评价

2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES) Pub Date : 2017-10-01 DOI:10.1109/INES.2017.8118571

M. Rojček, I. Černák, Róbert Janiga

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引用次数: 0

摘要

本文对两种模糊文本文档聚类算法进行了比较。首先是KMART算法，基于模糊ART神经网络的神经网络，第二种算法是基于K-Means算法的模糊C-Means。本文旨在比较两种算法在同时属于更多类别的真实、上下文相似的文本文档集上的质量和性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Quality and performance evaluation of the algorithms KMART and FCM for fuzzy clustering and categorization

In this paper we present a comparison of two fuzzy text document clustering algorithms. First of them is KMART algorithm, neural network based on Fuzzy ART neural network and the second algorithm is Fuzzy C-Means based on K-Means algorithm. The paper is aimed to compare the quality and performance of both algorithms on the set of real, contextually similar text documents falling into more categories at the same time.

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2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)

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