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Rule Extraction for Automatic Question Answering Based on Structural Clustering


Shen Song, Yu-N Cheah, Enya Kong Tang, Bali Ranaivo-Malan?on


Vol. 8  No. 3  pp. 208-215


Automatic question answering (QA) is playing an increasingly important role in intelligent answer searching. Many approaches have been employed for retrieving answers to natural language questions with rule-based approach being one of them. Traditionally, rules for automatic QA have been generated manually which may be time consuming and limited in scope. To address this issue, we present a proposed automatic rule extraction approach to generate rules for QA from training data via structural clustering.


Automatic question answering, rule extraction, structural clustering