Efficient Temporal Information Extraction from Korean Documents

Chae-Gyun Lim, Ho-Jin Choi

Abstract: As the amount of documents continues to increase steadily, it has become an important issue to shorten processing time in the field of natural language processing. In this paper, we describe a method to reduce the execution speed of the Korean temporal information extraction module from a development perspective. While the rule-based approach is useful for finding time representations from natural language sentences, the process of applying rules for each sentence can take a long time. In addition, in Korean sentences, the linguistic characteristics must be considered together to obtain exact temporal information. We first attempted to reduce the time to look for a time expression using the characteristics of the Korean morpheme, and then modified the module to speed up the search for the entire rule base. And we also show an experimental result that the change of execution speed according to the proposed approaches.