摘要
聊天机器人是当前网络机器人的一个热点问题。从在线论坛自动抽取〈帖子标题,回复〉对作为聊天知识,将粗糙集方法应用于相关回复的判断,同时结合基于Bagging的集成学习方法,进一步提高了识别效果。实验结果显示,抽取出来的〈帖子标题,回复〉对,具有较高的质量,可以作为聊天知识。
Chatbot is a hot issue in current web robots. In this paper chat knowledge is extracted from online discussion forums. Through analyzing replies with rough set technology,a reply classification model is designed. Further more ,ensemble learning based on bagging is applied here to improve the recognition results. The experimental results show that the extracted (thread-title ,reply) pairs have high quality and could be used as chat knowledge.
出处
《广西师范大学学报(自然科学版)》
CAS
北大核心
2008年第3期88-91,共4页
Journal of Guangxi Normal University:Natural Science Edition
基金
国家自然科学基金资助项目(60703010)
重庆市自然科学基金资助项目(2005BB2063)
重庆市教委科学技术研究基金资助项目(KJ050509)
关键词
聊天机器人
知识获取
粗糙集
集成学习
chatbot
knowledge acquisition
rough set
ensemble learning