基于图模块度的文本聚类与分类
Clustering and Classification in Text Collections Using Graph Modularity
摘要：
提出了一种新的文本文档聚类和分类的快速算法。该算法利用二分图实现了集合的词-文档矩阵。也就是说，二分图的模块度被用作优化泛函。使用新算法在一些文本集合上进行的实验显示了具有竞争力的聚类（分类）质量和破纪录的速度。
英文摘要：
A new fast algorithm for clustering and classification of large collections of text documents is introduced. The new algorithm employs the bipartite graph that realizes the word-document matrix of the collection. Namely, the modularity of the bipartite graph is used as the optimization functional. Experiments performed with the new algorithm on a number of text collections had shown a competitive quality of the clustering (classification), and a record-breaking speed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
