@inproceedings{goldhahn-quasthoff-2010-automatic,
title = "Automatic Annotation of Co-Occurrence Relations",
author = "Goldhahn, Dirk and
Quasthoff, Uwe",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/492_Paper.pdf",
abstract = "We introduce a method for automatically labelling edges of word co-occurrence graphs with semantic relations. Therefore we only make use of training data already contained within the graph. Starting point of this work is a graph based on word co-occurrence of the German language, which is created by applying iterated co-occurrence analysis. The edges of the graph have been partially annotated by hand with semantic relationships. In our approach we make use of the commonly appearing network motif of three words forming a triangular pattern. We assume that the fully annotated occurrences of these structures contain information useful for our purpose. Based on these patterns rules for reasoning are learned. The obtained rules are then combined using Dempster-Shafer theory to infer new semantic relations between words. Iteration of the annotation process is possible to increase the number of obtained relations. By applying the described process the graph can be enriched with semantic information at a high precision.",
}
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<abstract>We introduce a method for automatically labelling edges of word co-occurrence graphs with semantic relations. Therefore we only make use of training data already contained within the graph. Starting point of this work is a graph based on word co-occurrence of the German language, which is created by applying iterated co-occurrence analysis. The edges of the graph have been partially annotated by hand with semantic relationships. In our approach we make use of the commonly appearing network motif of three words forming a triangular pattern. We assume that the fully annotated occurrences of these structures contain information useful for our purpose. Based on these patterns rules for reasoning are learned. The obtained rules are then combined using Dempster-Shafer theory to infer new semantic relations between words. Iteration of the annotation process is possible to increase the number of obtained relations. By applying the described process the graph can be enriched with semantic information at a high precision.</abstract>
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%0 Conference Proceedings
%T Automatic Annotation of Co-Occurrence Relations
%A Goldhahn, Dirk
%A Quasthoff, Uwe
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F goldhahn-quasthoff-2010-automatic
%X We introduce a method for automatically labelling edges of word co-occurrence graphs with semantic relations. Therefore we only make use of training data already contained within the graph. Starting point of this work is a graph based on word co-occurrence of the German language, which is created by applying iterated co-occurrence analysis. The edges of the graph have been partially annotated by hand with semantic relationships. In our approach we make use of the commonly appearing network motif of three words forming a triangular pattern. We assume that the fully annotated occurrences of these structures contain information useful for our purpose. Based on these patterns rules for reasoning are learned. The obtained rules are then combined using Dempster-Shafer theory to infer new semantic relations between words. Iteration of the annotation process is possible to increase the number of obtained relations. By applying the described process the graph can be enriched with semantic information at a high precision.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/492_Paper.pdf
Markdown (Informal)
[Automatic Annotation of Co-Occurrence Relations](http://www.lrec-conf.org/proceedings/lrec2010/pdf/492_Paper.pdf) (Goldhahn & Quasthoff, LREC 2010)
ACL
- Dirk Goldhahn and Uwe Quasthoff. 2010. Automatic Annotation of Co-Occurrence Relations. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).