哈尔滨商业大学学报（自然科学版）2011，Vol.27Issue(1)：103-106,4.
一种基于Agent-NB的文本分类模型和算法
Model and algorithm of document classification based on Agent - NB
摘要
Abstract
Aim at the content-based document classification, a feedback classification model and algorithm was proposed, which combines the Agent and the Naive Bayes classification algorithm. Although the Bayesian algorithm was effective, the limited size of training sample set generally do not have good data completeness. It was difficult to construct a one-time classification model with high-performance. For the feedback classification algorithm based on Agent- NB, the classification performance was improved significantly by the intelligence of Agent, the feedback of classification information, and the dynamic adjustment of classification parameters. The experimental results showed that the algorithm had excellent classification ability, the recall rate, accuracy, and F1 values were satisfied.关键词
朴素贝叶斯分类/Agent-NB/文本分类算法Key words
naive bayes classification/ Agent- NB/ document classification algorithm分类
信息技术与安全科学引用本文复制引用
胡春娜,刘显德,郝兴..一种基于Agent-NB的文本分类模型和算法[J].哈尔滨商业大学学报（自然科学版）,2011,27(1):103-106,4.基金项目
国家自然科学基金(60572174) （60572174）
黑龙江省普通高等学校骨干教师创新能力资助计划项目(1055G002) （1055G002）
黑龙江省自然科学基金(ZA2006-11) （ZA2006-11）
黑龙江省科技攻关项目(GZ07A103). （GZ07A103）
