Konferenzbeitrag
Automatic Food Categorization from Large Unlabeled Corpora and Its Impact on Relation Extraction
We present a weakly-supervised induction method to assign semantic information to food items. We consider two tasks of categorizations being food-type classification and the distinction of whether a food item is composite or not. The categorizations are induced by a graph-based algorithm applied on a large unlabeled domain-specific corpus. We show that the usage of a domain-specific corpus is vital. We do not only outperform a manually designed open-domain ontology but also prove the usefulness of these categorizations in relation extraction, outperforming state-of-the-art features that include syntactic information and Brown clustering.
- Sprache
-
Englisch
Thema
Computerlinguistik
Ereignis
Geistige Schöpfung
(wer)
Wiegand, Michael
Roth, Benjamin
Klakow, Dietrich
Roth, Benjamin
Klakow, Dietrich
(wann)
2019-02-05
Ereignis
Veröffentlichung
(wer)
Stroudsburg, PA : Association for Computational Linguistics
- URN
-
urn:nbn:de:bsz:mh39-84696
- Letzte Aktualisierung
-
14.09.2023, 08:26 MESZ
Objekttyp
- Konferenzbeitrag
Beteiligte
- Wiegand, Michael
- Roth, Benjamin
- Klakow, Dietrich
- Stroudsburg, PA : Association for Computational Linguistics
Entstanden
- 2019-02-05
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