Discernibility Matrix and Rules Acquisition Based Chinese Question Answering System

Abstract

Different from English processing, Chinese text processing starts from word segmentation, and the results of word segmentation will influence the outcomes of subsequent processing especially in short text processing. In this paper, we introduce a novel method for Short Text Information Retrieval based Chinese Question Answering. It is developed from the Discernibility Matrix based Rules Acquisition method. Based on the acquired rules, the matching patterns of the training QA pairs can be represented by the reduced attribute words, and the words can also be represented by the QA patterns. Then the attribute words in the test QA pairs can be used to calculate the matching scores. The experimental results show that the proposed representation method of QA patterns has good flexibility to deal with the uncertainty caused by the Chinese word segmentation, and the proposed method has good performance at both MAP and MRR on the test data.