Centrality measures in text mining: prediction of noun phrases that appear in abstracts

Authors:
Zhuli Xie
Affiliations:
University of Illinois at Chicago, Chicago, IL
Venue:
ACLstudent '05 Proceedings of the ACL Student Research Workshop
Year:
2005

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Abstract

In this paper, we study different centrality measures being used in predicting noun phrases appearing in the abstracts of scientific articles. Our experimental results show that centrality measures improve the accuracy of the prediction in terms of both precision and recall. We also found that the method of constructing Noun Phrase Network significantly influences the accuracy when using the centrality heuristics itself, but is negligible when it is used together with other text features in decision trees.