@inproceedings{maynard-etal-2008-evaluating,
title = "Evaluating Evaluation Metrics for Ontology-Based Applications: Infinite Reflection",
author = "Maynard, Diana and
Peters, Wim and
Li, Yaoyong",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Tapias, Daniel",
booktitle = "Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}'08)",
month = may,
year = "2008",
address = "Marrakech, Morocco",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2008/pdf/273_paper.pdf",
abstract = "In this paper, we discuss methods of measuring the performance of ontology-based information extraction systems. We focus particularly on the Balanced Distance Metric (BDM), a new metric we have proposed which aims to take into account the more flexible nature of ontologically-based applications. We first examine why traditional Precision and Recall metrics, as used for flat information extraction tasks, are inadequate when dealing with ontologies. We then describe the Balanced Distance Metric (BDM) which takes ontological similarity into account. Finally, we discuss a range of experiments designed to test the accuracy and usefulness of the BDM when compared with traditional metrics and with a standard distance-based metric.",
}
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<abstract>In this paper, we discuss methods of measuring the performance of ontology-based information extraction systems. We focus particularly on the Balanced Distance Metric (BDM), a new metric we have proposed which aims to take into account the more flexible nature of ontologically-based applications. We first examine why traditional Precision and Recall metrics, as used for flat information extraction tasks, are inadequate when dealing with ontologies. We then describe the Balanced Distance Metric (BDM) which takes ontological similarity into account. Finally, we discuss a range of experiments designed to test the accuracy and usefulness of the BDM when compared with traditional metrics and with a standard distance-based metric.</abstract>
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%0 Conference Proceedings
%T Evaluating Evaluation Metrics for Ontology-Based Applications: Infinite Reflection
%A Maynard, Diana
%A Peters, Wim
%A Li, Yaoyong
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Tapias, Daniel
%S Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)
%D 2008
%8 May
%I European Language Resources Association (ELRA)
%C Marrakech, Morocco
%F maynard-etal-2008-evaluating
%X In this paper, we discuss methods of measuring the performance of ontology-based information extraction systems. We focus particularly on the Balanced Distance Metric (BDM), a new metric we have proposed which aims to take into account the more flexible nature of ontologically-based applications. We first examine why traditional Precision and Recall metrics, as used for flat information extraction tasks, are inadequate when dealing with ontologies. We then describe the Balanced Distance Metric (BDM) which takes ontological similarity into account. Finally, we discuss a range of experiments designed to test the accuracy and usefulness of the BDM when compared with traditional metrics and with a standard distance-based metric.
%U http://www.lrec-conf.org/proceedings/lrec2008/pdf/273_paper.pdf
Markdown (Informal)
[Evaluating Evaluation Metrics for Ontology-Based Applications: Infinite Reflection](http://www.lrec-conf.org/proceedings/lrec2008/pdf/273_paper.pdf) (Maynard et al., LREC 2008)
ACL