TY - CHAP U1 - Konferenzveröffentlichung A1 - Wiegand, Michael A1 - Roth, Benjamin A1 - Klakow, Dietrich ED - Biemann, Chris ED - Handschuh, Siegfried ED - Freitas, André ED - Meziane, Farid ED - Métais, Elisabeth T1 - Combining Pattern-Based and Distributional Similarity for Graph-Based Noun Categorization T2 - Natural Language Processing and Information Systems. Proceedings of the 20th International Conference on Applications of Natural Language to Information Systems, NLDB 2015, Passau, Germany, June 17–19, 2015 N2 - We examine the combination of pattern-based and distributional similarity for the induction of semantic categories. Pattern-based methods are precise and sparse while distributional methods have a higher recall. Given these particular properties we use the prediction of distributional methods as a back-off to pattern-based similarity. Since our pattern-based approach is embedded into a semi-supervised graph clustering algorithm, we also examine how distributional information is best added to that classifier. Our experiments are carried out on 5 different food categorization tasks. T3 - Lecture Notes in Computer Science - 9103 KW - Lebensmittel KW - Computerlinguistik KW - Maschinelles Lernen KW - Information Extraction KW - Grafische Darstellung KW - Food item KW - Neighbour classifier KW - Graph cluster KW - Relation extraction KW - Unconnected node Y1 - 2015 UN - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-87479 SN - 978-3-319-19580-3 SB - 978-3-319-19580-3 U6 - https://doi.org/10.1007/978-3-319-19581-0_5 DO - https://doi.org/10.1007/978-3-319-19581-0_5 N1 - Dieser Beitrag ist aus urheberrechtlichen Gründen online nicht frei zugänglich. SP - 64 EP - 72 PB - Springer CY - Cham ER -