文章基本信息

标题：Matching and merging anonymous terms from web sources
本地全文：下载
作者：Kun Ji ; Shanshan Wang ; Lauri Carlson 等
期刊名称：International Journal of Web & Semantic Technology
印刷版ISSN：0976-2280
电子版ISSN：0975-9026
出版年度：2014
卷号：5
期号：4
页码：53
DOI：10.5121/ijwest.2014.5304
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：This paper describes a workflow of simplifying and matching special language terms in RDF generatedfrom trawling term candidates from Web terminology sites with TermFactory, a Semantic Web frameworkfor professional terminology. Term candidates from such sources need to be matched and eventually mergedwith resources already in TermFactory. While merging anonymous data, it is important not to lose track ofprovenance. For coding provenance in RDF, TF uses a minor but apparently novel variant of RDFreification. In addition, TF implements a toolkit of methods for dealing with graphs containing anonymous(blank) nodes.
关键词：RDF; provenance; anonymous/blank nodes; LSP; professional terminology work