Refining Terminological Saturation using String Similarity Measures
This paper reports on the refinement of the THD algorithm, developed in the OntoElect framework. This baseline THD algorithm used exact string matches for key term comparison. It has been refined by introducing an appropriate string similarity metric for grouping the terms having similar meaning and looking similar as text strings. To choose the most appropriate metric, several existing metrics have been cross evaluated on the developed test set of multiword terms in English. The rationale for creating this test set is also presented. Further, the refined algorithm for measuring terminological difference has been cross evaluated with the baseline THD algorithm. For this cross evaluation, the bags of terms extracted from the TIME collection of scientific papers were used. The experiment revealed that using the refined algorithm yielded better and quicker terminological saturation, compared to the baseline.
ICTERI