Matching and Merging Anonymous Terms from Web Sources

Kun Ji, Shanshan Wang, Lauri Carlson

    Research output: Contribution to journalArticleScientificpeer-review


    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.
    Original languageEnglish
    Article numberNo.4
    JournalInternational journal of web and semantic technology
    Issue number4
    Pages (from-to)53-69
    Number of pages17
    Publication statusPublished - Oct 2014
    MoE publication typeA1 Journal article-refereed

    Fields of Science

    • 222 Other engineering and technologies
    • RDF
    • provenance
    • anonymous/blank nodes
    • LSP
    • professional terminology work

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