文档聚类综述

A Survey of Document Clustering

聚类作为一种自动化程度较高的无监督机器学习方法,近年来在信息检索、多文档自动文摘等领域获得了广泛的应用。本文首先讨论了文档聚类的应用背景和体系结构,然后对文档聚类算法、聚类空间的构造和降维方法、文档聚类中的语义问题进行了综述。最后还介绍了聚类质量评测问题。

As an unsupervised machine learning method, document clustering has been widely used in many NLP applications such as information retrieval, automatic multi-document summarization and etc. In this paper the background and the architecture of document clustering is discussed firstly, and then some related problems are surveyed which includes clustering algorithm, feature space construction, dimension reduction and the semantic problem. In the end this paper introduces the evaluation of cluster quality.