Data Management

SITAC: Discovering Semantically Identical Temporally Altering Concepts in Text Archives

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Executive Summary

This paper demonstrates a system called SITAC based on the authors' proposed approach to automate the discovery of concepts (called SITACs) in text sources that are identical semantically but alter their names over time. This system is developed to perform time-aware translation of queries over text corpora by incorporating terminology evolution, thus providing more accurate responses to users, e.g., query processing on Mumbai should automatically take into account its former name Bombay. The SITAC system constitutes a novel collaborative framework of natural language processing, association rule mining and contextual similarity.

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