Extraction of Daily Changing Words for Question Answering

This paper proposes a method for extracting Daily Changing Words (DCWs), words that indicate which questions are realtime dependent. Our approach is based on two types of template matching using time and named entity slots from large size corpora and adding simple filtering methods from news corpora. Extracted DCWs are utilized for detecting and sorting real-time dependent questions. Experiments confirm that our DCWmethod achieves higher accuracy in detecting real-time dependent questions than existing word classes and a simple supervised machine learning approach.