| 摘要: |
| 海量信息的模式提取是网络环境下海量信息集成研究的难点.给出了一种新的局部精确模式提取及其增量保持方法,通过探测目标集的路径距离,利用Hash类及其路径距离操作,将模式的生成规模控制在"模式直径"范围内,从而有效地抑制了模式膨胀. |
| 关键词: 海量信息 半结构化数据 模式提取 数据模型 信息集成 |
| DOI： |
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| 基金项目:国家重点基础研究发展规划973资助项目(G1999032705);北京大学-IBM创新研究院资助项目 |
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| Extracting Local Schema from Massive Information in Network Environment |
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WANG Teng jiao,TANG Shi wei,YANG Dong qing,LIU Yun feng
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| Abstract: |
| Extracting schema from massive information is very difficult for the research on massive information integration in network environment. A new method is presented in this paper, which is about extracting and incremental maintenance of local accurate schema. In this process, the algorithm control the scale of extracted schema within the 'schema diameter' by examining the path distance of the target set and using the Hash class and its path distance operation. This method is very efficient for restrain schema from expanding. |
| Key words: global information semi structured data extracting schema data model information integration |
