计算机工程2011，Vol.37Issue(24)：161-163,3.DOI:10.3969/j.issn.1000-3428.2011.24.054
基于非负矩阵分解的双重约束文本聚类算法
Dual-constraints Text Clustering AlgorithmBased on Non-negative Matrix Factorization
摘要
Abstract
Non-negative Matrix Factorization(NMF) with dual constraints method for document clustering is proposed. It is based on NMF model with adding of pair-wise constraints on documents and categorization constraints of the words. Iterative rules obtained from the original word-document matrix are decomposed to get document clustering results. Compared with a variety of popular semi-supervised clustering algorithm, the method for document clustering can effectively improve the accuracy of document clustering, and can provide more accurate and efficient clustering results.关键词
半监督聚类/非负矩阵分解/成对约束/类别约束Key words
semi-supervised clustering/ Non-negative Matrix Factorization(NMF)/ pairwise constraint/ category constraint分类
信息技术与安全科学引用本文复制引用
马慧芳,赵卫中,史忠植..基于非负矩阵分解的双重约束文本聚类算法[J].计算机工程,2011,37(24):161-163,3.基金项目
国家自然科学基金资助项目(61105052,61163039) （61105052,61163039）
西北师范大学青年教师科研能力提升计划基金资助项目"面向Web的主题建模关键技术研究"(NWN U-LKQN-10-1) （NWN U-LKQN-10-1）
湘潭大学博士启动基金资助项目(10QDZ42) （10QDZ42）
