摘要
设计和实现了一个基于本体的项目和领域专家匹配原型系统。首先在集成基于点和基于边的语义相似度计算方法的基础上,提出一种计算两棵树型概念结构中两个概念节点之间以及两棵树型概念结构之间的语义相似度的方法;然后以项目文档和领域专家文档匹配为实例,按照相似度大小排序,为一个项目选择合适的评审专家。测试结果表明,所提出的方法及实现的系统原型可以在较大程度上拟合人工判断,获得较高的准确率和召回率,为评审项目时选择合适的领域专家提供了一个新的思路。
This paper designed and implemented a ontology-based prototype system for projects and domain experts matching. To begin with, based on the node-based approach and edge-based approach, presented an integrated approach to calculate the semantic similarity between two nodes in two concepts trees and between two concept trees. Then selected the proper domain expert for one given project according to the ranking of semantic similarities between project documents and domain expert documents. The final results of the tests show that the presented approach and implemented system can get better recall and precision. This kind of method presents a novel idea for matching projects and domain experts.
出处
《计算机应用研究》
CSCD
北大核心
2009年第10期3787-3790,共4页
Application Research of Computers
基金
国家自然科学基金重点资助项目(7043100170771019)
关键词
本体
语义相似度
匹配系统
ontology
semantic similarity
matching system
