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Experimental evaluation of ranking and selection methods in term extraction

  • Hiroshi Nakagawa
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Abstract

An automatic term extraction system consists of a term candidate extraction subsystem, a ranking subsystem and a selection subsystem. In this paper, we experimentally evaluate two ranking methods and two selection methods. As for ranking, a dichotomy of unithood and termhood is a key notion. We evaluate these two notions experimentally by comparing Imp based ranking method that is based directly on termhood and C-value based method that is indirectly based on both termhood and unithood. As for selection, we compare the simple threshold method with the window method that we propose. We did the experimental evaluation with several Japanese technical manuals. The result does not show much difference in recall and precision. The small difference between the extracted terms by these two ranking methods depends upon their ranking mechanism per se.

Abstract

An automatic term extraction system consists of a term candidate extraction subsystem, a ranking subsystem and a selection subsystem. In this paper, we experimentally evaluate two ranking methods and two selection methods. As for ranking, a dichotomy of unithood and termhood is a key notion. We evaluate these two notions experimentally by comparing Imp based ranking method that is based directly on termhood and C-value based method that is indirectly based on both termhood and unithood. As for selection, we compare the simple threshold method with the window method that we propose. We did the experimental evaluation with several Japanese technical manuals. The result does not show much difference in recall and precision. The small difference between the extracted terms by these two ranking methods depends upon their ranking mechanism per se.

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