基于本体的语义搜索模型研究

Chongchong Zhao, Jing Wang, Wei Hu, X. Yu, Xiaofeng Wang
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引用次数: 4

摘要

随着数据的爆炸式增长,如何准确有效地检索信息成为人们关注的焦点。为了解决这一问题,研究者们提出了各种各样的语义检索模型。本文提出了一种改进的基于本体的语义相似度计算模型SDDP(Semantic, Density, Distance, Property),该模型综合考虑了语义密度、语义深度、语义距离和基于属性的相似度计算等因素。实验证明,该模型在查全率和查准率方面比其他模型有更大的提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An ontology-based semantic search model study
With the explosion of data growth, the problem how to retrieve information accurately and effectively comes into focus. To address this issue, researchers have put forward a variety of semantic retrieval models. This paper presents SDDP(Semantic, Density, Distance, Property) model which is an improved ontology-based semantic similarity calculation, and in this model the factors, such as semantic density, semantic depth, semantic distance and the attribute-based similarity calculation, are all involved. It was proved by experiment that the model has more improvement than other models in the recall and precision ratio.
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