Mapping Collocational Properties into Machine Learning Features (1998)
| Citations: | 11 - 6 self |
BibTeX
@MISC{Wiebe98mappingcollocational,
author = {Janyce M. Wiebe and Kenneth J. McKeever and Rebecca F. Bruce},
title = {Mapping Collocational Properties into Machine Learning Features},
year = {1998}
}
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Abstract
This paper investigates interactions between collocational properties and methods for orga- nizing them into features for machine learn- ing. In experiments performing an event categorization task, Wiebe et al. (1997a) found that different organizations are best for dif- ferent properties. This paper presents a sta- tistical analysis of the results across different machine learning algorithms. In the experiments, the relationship between property and organization was strikingly consistent across algorithms. This prompted further analysis of this relationship, and an investigation of criteria for recognizing beneficial ways to include collocational properties in machine learning ex- periments. While many types of collocational properties and methods of organizing them into features have been used in NLP, systematic in- vestigations of their interaction are rare.
