摘要
以图书馆的常见问题为基础,研究全文检索、中文分词、向量空间模型等技术,构建符合相关问题的知识库,结合云数据库设计,在微信小程序平台运用JavaScript,WXML,WXSS,Python等开发语言和Flask框架,实现一个基于微信小程序的图书馆智能客服系统,其中的智能回复模块实现了全文检索和中文分词等技术,以鲜明的便捷性、开放性和自主性拓宽了图书馆的智能服务模式.
Based on the common problems of the library,this paper studies the full-text retrieval,Chinese word segmentation,vector space model and other technologies,builds a knowledge base that meets the relevant problems.Combined with the cloud database design,it uses JavaScript,WXML,WXSS,Python and other development languages and flag framework in wechat applet platform to realize a library intelligent customer service system based on wechat small program The reply module realizes full-text retrieval and Chinese word segmentation technology,which widens the intelligent service mode of library with its distinct convenience,openness and autonomy.
作者
杨柳
吴彦蓉
YANG Liu;WU Yanrong(College of Computer and Electronic Information,Guangxi University,Nanning 530004,China;China State Railway Nanning Group Co.,Ltd Information Technology Institute,Nanning 530029,China)
出处
《太原师范学院学报（自然科学版）》
2021年第1期65-68,共4页
Journal of Taiyuan Normal University:Natural Science Edition
基金
广西自然科学基金项目(20181097):面向跨域协作的物联网动态信任模型与方法研究.
关键词
全文检索
中文分词
向量空间模型
图书馆智能客服
微信小程序
full text search
Chinese word segmentation
vector space model
library intelligent customer service
wechat applet
