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机构地区:[1]中国农业大学信息与电气工程学院,北京100083
出 处:《计算机与数字工程》2015年第10期1746-1750,共5页Computer & Digital Engineering
摘 要:本体分为轻量级本体和重量级本体,轻量级本体主要由术语、概念、分类关系构成。在轻量级本体的基础上添加非分类关系和公理构成重量级本体。前者侧重于知识结构表达而缺乏语义和逻辑推理功能,后者具有较强的语义和逻辑推理功能,更适合信息的语义处理和新知识的发现。论文按照逆反公理和对称公理的语言模式构造原有非分类关系的模式,然后利用轻量级本体对生成的模式进行扩展,同时结合使用统计学中共现值的方法,最终达到抽取农业病虫害领域的公理。抽取公理中模式的扩展利用了轻量级本体,提高了公理抽取的效果。此外,论文将公理抽取的方法应用于中文领域,抽取中文语料的逆反公理和对称公理。Ontology is divided into lightweight and heavyweight ontology,lightweight ontology consists of terminology,concepts and classification of relationships.Heavyweight ontology is constituted by adding non-taxonomic relationship and axiom on the basis of a lightweight ontology.The former focuses on the knowledge structure of expression,but the latter has stronger semantic and logical reasoning function,which is more suitable for the semantic processing of information and the discovery of new knowledge.According to the reverse and symmetric axiom of language schema,the original non-taxonomic relationship model is constructed,and then extends of the generated model by using a lightweight ontology.At the same time,combined with the party's present value method of statistics,this approach extracts axioms in the field of agricultural plant diseases and insect pests,and only improves the efficiency of axiom,but has been applied in the field of Chinese Language to extract of the reverse axiom and symmetric axiom.
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