TY - CHAP U1 - Konferenzveröffentlichung A1 - Wiegand, Michael A1 - Roth, Benjamin A1 - Klakow, Dietrich ED - Jancsary, Jeremy T1 - Data-driven Knowledge Extraction for the Food Domain T2 - Proceedings of the 11th Conference on Natural Language Processing (KONVENS 2012). Empirical Methods in Natural Language Processing, September 19-21, 2012, Vienna, Austria N2 - In this paper, we examine methods to automatically extract domain-specific knowledge from the food domain from unlabeled natural language text. We employ different extraction methods ranging from surface patterns to co-occurrence measures applied on different parts of a document. We show that the effectiveness of a particular method depends very much on the relation type considered and that there is no single method that works equally well for every relation type. We also examine a combination of extraction methods and also consider relationships between different relation types. The extraction methods are applied both on a domain-specific corpus and the domain-independent factual knowledge base Wikipedia. Moreover, we examine an open-domain lexical ontology for suitability. T3 - Schriftenreihe der Österreichischen Gesellschaft für Artificial Intelligence (ÖGAI) - Band 5 KW - Information Extraction KW - Computerlinguistik KW - Korpus KW - Empirische Linguistik KW - Lebensmittel Y1 - 2012 U6 - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-84529 UN - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-84529 UR - http://www.oegai.at/konvens2012/proceedings.shtml SN - 3-85027-005-X SB - 3-85027-005-X SP - 21 EP - 29 PB - Österreichische Gesellschaft für Artificial Intelligence CY - Wien ER -