Web-Based Relation Extraction for the Food Domain

In this paper, we examine methods to extract different domain-specific relations from the food domain. 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. As we need to process a large amount of unlabeled data our methods only require a low level of linguistic processing. This has also the advantage that these methods can provide responses in real time.

Metadaten
Author:	Michael Wiegand GND, Benjamin Roth, Dietrich Klakow
URN:	urn:nbn:de:bsz:mh39-87454
DOI:	https://doi.org/10.1007/978-3-642-31178-9_25
ISBN:	978-3-642-31177-2
Parent Title (English):	Natural Language Processing and Information Systems. Proceedings of the 17th International Conference on Applications of Natural Language to Information Systems, NLDB 2012, Groningen, The Netherlands, June 26-28, 2012
Series (Serial Number):	Lecture Notes in Computer Science (7337)
Publisher:	Springer
Place of publication:	Berlin [u.a.]
Editor:	Gosse Bouma, Ashwin Ittoo, Elisabeth Métais, Hans Wortmann
Document Type:	Conference Proceeding
Language:	English
Year of first Publication:	2012
Date of Publication (online):	2019/04/02
Tag:	Food item; Linguistic processing; Mean reciprocal rank; Relation type; Sparkling wine
GND Keyword:	Computerlinguistik; Information Extraction; Lebensmittel; Natürliche Sprache
First Page:	222
Last Page:	227
Note:	Dieser Beitrag ist aus urheberrechtlichen Gründen online nicht frei zugänglich.
DDC classes:	400 Sprache / 400 Sprache, Linguistik
Open Access?:	nein
Licence (German):	Urheberrechtlich geschützt

Open Access