Search-based Entity Disambiguation with Document-Centric Knowledge Bases

Stefan Zwicklbauer, Christin Seifert, Michael Granitzer

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Abstract

    Entity disambiguation is the task of mapping ambiguous terms in natural-language text to its entities in a knowledge base. One possibility to describe these entities within a knowledge base is via entity-annotated documents (document-centric knowledge base). It has been shown that entity disambiguation with search-based algorithms that use document-centric knowledge bases perform well on the biomedical domain. In this context, the question remains how the quantity of annotated entities within documents and the document count used for entity classification influence disambiguation results. Another open question is whether disambiguation results hold true on more general knowledge data sets (e.g. Wikipedia). In our work we implement a search-based, document-centric disambiguation system and explicitly evaluate the mentioned issues on the biomedical data set CALBC and general knowledge data set Wikipedia, respectively. We show that the number of documents used for classification and the amount of annotations within these documents must be well-matched to attain the best result. Additionally, we reveal that disambiguation accuracy is poor on Wikipedia. We show that disambiguation results significantly improve when using shorter but more documents (e.g. Wikipedia paragraphs). Our results indicate that search-based, document-centric disambiguation systems must be carefully adapted with reference to the underlying domain and availability of user data.
    Original languageEnglish
    Title of host publicationi-KNOW'15. Proceedings of the 14th International Conference on Knowledge Management and Knowledge Technologies (I-Know)
    PublisherACM Press
    ISBN (Print)978-1-4503-3721-2
    DOIs
    Publication statusPublished - 1 Oct 2015
    Event15th International Conference on Knowledge Technologies and Data-driven Business - Graz, Austria
    Duration: 21 Oct 201522 Oct 2015
    Conference number: 15th

    Conference

    Conference15th International Conference on Knowledge Technologies and Data-driven Business
    Abbreviated titlei-KNOW 2015
    CountryAustria
    CityGraz
    Period21/10/1522/10/15

    Fingerprint Dive into the research topics of 'Search-based Entity Disambiguation with Document-Centric Knowledge Bases'. Together they form a unique fingerprint.

    Cite this