Crowdsourcing Fact Extraction from Scientific Literature

Christin Seifert, Michael Granitzer, Patrick Hoefler, Belgin Mutlu, Vedran Sabol, Kai Schlegel, Sebastian Bayerl, Florian Stegmaier, Stefan Zwicklbauer, Roman Kern

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

    8 Citations (Scopus)


    Scientific publications constitute an extremely valuable body of knowledge and can be seen as the roots of our civilisation. However, with the exponential growth of written publications, comparing facts and findings between different research groups and communities becomes nearly impossible. In this paper, we present a conceptual approach and a first implementation for creating an open knowledge base of scientific knowledge mined from research publications. This requires to extract facts - mostly empirical observations - from unstructured texts (mainly PDF’s). Due to the importance of extracting facts with high-accuracy and the impreciseness of automatic methods, human quality control is of utmost importance. In order to establish such quality control mechanisms, we rely on intelligent visual interfaces and on establishing a toolset for crowdsourcing fact extraction, text mining and data integration tasks.
    Original languageEnglish
    Title of host publicationHuman-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data
    Subtitle of host publicationThird International Workshop, HCI-KDD 2013, Held at SouthCHI 2013, Maribor, Slovenia, July 1-3, 2013. Proceedings
    EditorsAndreas Holzinger, Gabriella Pasi
    Number of pages13
    Publication statusPublished - 1 Jul 2013
    EventHCI-KDD@SouthCHI 2013: Human-Computer Interaction & Interactive Knowledge Discovery - Maribor, Slovenia
    Duration: 1 Jul 20133 Jul 2013

    Publication series

    NameLecture Notes in Computer Science


    ConferenceHCI-KDD@SouthCHI 2013


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