摘要
研究了从数据密集型Web页面中自动提取结构化数据并形成知识表示系统的问题。基于知识数据库实现动态页面获取,进行预处理后转换为XML文档,采用基于PAT-array的模式发现算法自动发现重复模式,结合基于本体的关键词库自动识别页面数据显示结构模型,利用XML的对象-关系映射技术将数据存入知识数据库,由此实现Web数据自动抽取。同时,利用知识数据库已有知识从互联网抽取新知识,达到知识数据库的自扩展。以交通信息自动抽取及混合交通出行方案生成与表示系统进行的实验表明该系统具有高抽取准确率和良好的适应性。
The Web Information Extraction and Knowledge Presentation System is proposed to extract information from data intensive web pages.It downloads dynamic web pages, based on a knowledge database, changes them to XML documents after preprocessing, finds repeated patterns from them, by using a PAT-array based Pattern Discovery Algorithm, recognizes their data display structure models, automatically based on the repeated patterns and an ontology-based keyword library, and then extracts the data and stores them in the knowledge database with the object-relational mapping technology of XML.Through these steps, web data is extracted automatically, and the knowledge database is also expanded automatically.Experiments on the traffic information auto-extraction and mixed traffic travel schemes auto-creation system showed that the system has high precision and is adaptive to web pages in different domains with different structures.
出处
《计算机系统应用》
2010年第9期1-4,9,共5页
Computer Systems & Applications
基金
安徽省教育厅自然科学基金(2005KJ004ZD)
