Evaluating Evaluation Metrics for Ontology-Based Applications: Infinite Reflection

9727

Authors

nan

Abstract

AbstractIn 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.

Keywords

nan

Full Content

nan

Labeled Text

AbstractIn 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.

Publication Details

Paper ID:
9727
Year:
2008
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan