【摘要】 如何从网上海量信息中发现有用的知识,满足使用者的需要是一个迫切需要研究的课题。但现有的方法很难从Web上把大量非结构信息抽取到数据库中,而且一般的搜索引擎也只是简单地把关键字匹配作为查询依据,命中率较低。文章提出了将自然语言理解技术与Web数据挖掘相结合,根据用户的需要定制个性化的Web数据挖掘模型。初步试验结果表明该方案是可行的,能很好的满足用户需要,且模型的通用性和适用性强。更多还原

【Abstract】 It is an urgent problem as to how to find the useful knowledge meeting the needs of the users on the Internet. The general search engine is based on keywords querying and its accuracy is low. But it is difficult to extract lots of structureless information from the Web into the database with existing methods. This paper proposes a method of applying nature language understanding technology to Web mining and designing personalized Web mining model to meet the needs of a particular user. We have implemented it. It indicates that the model is feasible and can meet well the need of the users. This model can be applied to other specific fields easily.更多还原