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Ontology Enrichment based on Generic Basis of Association Rules for Conceptual Document Indexing

机译:基于概念文件索引的关联规则的通用基础本体富集

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In this paper, we propose the use of a minimal generic basis of association rules (ARs) between terms, in order to automatically enrich an initial domain ontology. For this purpose, three distance measures are defined to link the candidate terms identified by ARs, to the initial concepts in the ontology. The final result is a proxemic conceptual network which contains additional implicit knowledge. Therefore, to evaluate our ontology enrichment approach, we propose a novel document indexing approach based on this proxemic network. The experiments carried out on the OHSUMED document collection of the TREC 9 filtring track and MeSH ontology showed that our conceptual indexing approach could considerably enhance information retrieval effectiveness.
机译:在本文中,我们建议在术语之间使用关联规则(ARS)的最小通用基础,以便自动丰富初始域本体。为此目的,定义了三个距离措施,以将由ARS标识的候选术语链接到本体中的初始概念。最终结果是一个概念概念网络,包含额外的隐式知识。因此,为了评估我们的本体丰富方法,我们提出了一种基于此接受网络的新型文档索引方法。在TREC 9滤波器轨道和网眼本体的OHSUMED文件集合上进行的实验表明,我们的概念分度方法可以大大提高信息检索效率。

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