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词汇关联性的实证研究及其在推荐系统中的应用

An Empirical Study of Vocabulary Relatedness and Its application to Recommender Systems
课程网址: http://videolectures.net/iswc2011_cheng_study/  
主讲教师: Gong Cheng
开课单位: 南京大学
开课时间: 2011-11-25
课程语种: 汉简
中文简介:
当成千上万的词汇被不同的权威机构发布在语义网上时,一个问题出现了,它们是如何相互联系的。现有工作主要分析了它们的相似性。本文从语义关联性、词汇内容相似性、表达紧密性和分布关联性四个角度考察了关联性的一般概念。我们在一个包含2996个词汇和1500万个使用它们的RDF文档的大型真实数据集上对这些度量进行了实证研究。然后,我们提出将词汇相关性应用于后选择词汇推荐问题。我们将这种推荐服务作为词汇搜索引擎的一部分来实现,并根据手工制作的黄金标准来测试其有效性。
课程简介: When thousands of vocabularies having been published on the SemanticWeb by various authorities, a question arises as to how they are related to each other. Existing work has mainly analyzed their similarity. In this paper, we inspect the more general notion of relatedness, and characterize it from four angles: well-defined semantic relatedness, lexical similarity in contents, closeness in expressivity and distributional relatedness. We present an empirical study of these measures on a large, real data set containing 2,996 vocabularies, and 15 million RDF documents that use them. Then, we propose to apply vocabulary relatedness to the problem of post-selection vocabulary recommendation. We implement such a recommender service as part of a vocabulary search engine, and test its effectiveness against a handcrafted gold standard.
关 键 词: 语义网; 关联性; 相似性; 词汇搜索引擎
课程来源: 视频讲座网
最后编审: 2019-12-19:lxf
阅读次数: 51