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An approach of web text information filtering based on domain ontology to expand users' requirements

机译:一种基于领域本体扩展用户需求的Web文本信息过滤方法

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Semantic-based information filtering has become a hotspot in text filtering field. Based on the research of traditional text information filtering method which includes too little semantic information to represent user requirements and be understood by the computer, and leads the filtering result not to coincidence of user demands as well as significant influence on filtration performance. This paper presents a web text information filtering method that employs domain ontology to extend customer requirements aiming at these problems. This method includes the semantic extension of user profile based on domain-ontology as well as expression, and the matching algorithm of user demand and the file waiting to be filtered. Firstly, check whether the user requirements belong to domain ontology according to membership degree. Subsequently, deduce and extend the meaning of user demand on the basis of concept description, relational definition and rules of domain ontology. Finally, match document and user demand vector representation after expressing user requirements and file waiting to be filtered by vector space model. The experiment showed this approach can yields good effect on information filtering.
机译:基于语义的信息过滤已经成为文本过滤领域的热点。在对传统文本信息过滤方法的研究基础上,该方法过滤的语义信息太少,不足以代表用户需求,无法被计算机理解,导致过滤结果不符合用户需求,对过滤性能的影响较大。本文提出了一种网络文本信息过滤方法,该方法采用领域本体来扩展针对这些问题的客户需求。该方法包括基于领域本体和表达式的用户配置文件的语义扩展,以及用户需求和等待过滤的文件的匹配算法。首先,根据隶属度检查用户需求是否属于领域本体。随后,在概念描述,关系定义和领域本体规则的基础上,推论和扩展了用户需求的含义。最后,在表达用户需求和文件等待向量空间模型过滤之后,匹配文档和用户需求向量表示。实验表明,该方法可以对信息过滤产生良好的效果。

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