计算机科学 ›› 2016, Vol. 43 ›› Issue (9): 82-86.doi: 10.11896/j.issn.1002-137X.2016.09.015
• 2015 年第三届CCF 大数据学术会议 • 上一篇 下一篇
朱建林,杨小平,彭鲸桥
ZHU Jian-lin, YANG Xiao-ping and PENG Jing-qiao
摘要： 为了在不加入外部语义知识的前提下改善向量空间模型的文本分类效果,通过挖掘语料库内部蕴含的词间关系和文本间关系,并以不同的方式融入原始的词文本矩阵,然后选择常用的SVM和KNN算法,在领域性较强的法律语料库和领域性较宽泛的新闻语料库上进行文本分类的对比实验。实验证明,加入词间关系和文本间关系通常能有效改善文本分类的效果,但是对不同的分类方法和领域特征有不同的影响,在实际应用中应该区别对待。
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