Matching and merging anonymous terms from web sources

Autor:	Shanshan Wang, Lauri Carlson, Kun Ji
Rok vydání:	2014
Předmět:	Workflow Information retrieval Computer science RDF Schema computer.file_format RDF Semantic Web computer Blank RDF/XML Terminology Coding (social sciences)
Zdroj:	University of Helsinki
ISSN:	0975-9026 0976-2280
DOI:	10.5121/ijwest.2014.5404
Popis:	This paper describes a workflow of simplifying and matching special language terms in RDF generated from trawling term candidates from Web terminology sites with TermFactory, a Semantic Web framework for professional terminology. Term candidates from such sources need to be matched and eventually merged with resources already in TermFactory. While merging anonymous data, it is important not to lose track of provenance. For coding provenance in RDF, TF uses a minor but apparently novel variant of RDF reification. In addition, TF implements a toolkit of methods for dealing with graphs containing anonymous (blank) nodes.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ab0a67c232765182e4fd5ea70165a7d https://doi.org/10.5121/ijwest.2014.5404 Zobrazit plný text záznamu