基于Web的制造信息主动推荐服务研究  

Manufacturing information active recommendation based on Web services

作　　者：方辉[1] 谭建荣[1] 谭颖[2] 冯毅雄[1] 

机构地区：[1]浙江大学CAD&CG国家重点实验室,浙江杭州310027 [2]四川大学制造科学与工程学院,四川成都610065

出　　处：《计算机集成制造系统》2008年第11期2253-2260,共8页Computer Integrated Manufacturing Systems

基　　金：国家863/CI MS主题资助项目(2007AA04Z190,2008AA042301);国家科技支撑计划资助项目(2006BAF01A37)~~

摘　　要：针对目前企业信息系统较少考虑不同人员对信息的不同需求的问题,提出通过制造信息主动推荐服务,达到将适当信息及时准确地传递给适当人员的目标。分析了网络环境下制造信息获取方式及其对主动推荐服务的需求,构建了信息推荐服务结构体系。提出运用主动学习和被动学习方式获取用户兴趣,定义了制造信息内容需求的结构形式,提出了基于词距离方法的制造信息资源相似度计算模型和以关键词表示的相关度计算模型,并通过文档对象模型树形结构,获取以可扩展标记语言关键词表示的制造信息语料并形成语料库,实现符合用户兴趣的相似Web页面判断和收集,通过丰富站点摘要技术,实现制造信息的主动推荐服务,从而提高企业网络信息服务质量,增强企业对动态信息的响应能力。Existing enterprises＇ information systems seldom take differenet requirement tendency of different personnel into consideration, the idea of Manufacturing Information Active Recommendation （MIAR） was put forward to transfer proper information to proper personnel correctly and timely. Through analyzing methods of manufacturing information acquirement in Web environment and its requirement for active recommendation service, the architecture of MIAR service was constructed. By active learning and passive learning methods, users＇ interest toward specific information were acquired, and content requirement structure of manufacturing information was also defined. To analyze Web pages, similarity computing model based on words distance and relevancy computing model based on key words was proposed. Manufacturing information corpus buildup by eXtensible Markup Language （XML） key words from tree structures of Document Object Module （DOM） was obtained so as to judge and collect similar Web pages according to users＇ interest. The MIAR was implemented by Rich Site Summary （RSS） to improve enterprises information systems＇ service quality and strengthen enterprises＇ response to dynamic information.

关 键 词：WEB服务 制造信息 主动推荐 信息系统 用户兴趣获取 丰富站点摘要 

分 类 号：TH162[机械工程—机械制造及自动化]