文章基本信息

标题：Car FAQ Assistant Based on BILSTM-Siamese Network
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作者：Bo Jin ; Zhezhi Jin
期刊名称：Open Access Library Journal
印刷版ISSN：2333-9705
电子版ISSN：2333-9721
出版年度：2019
卷号：6
期号：10
页码：1-7
DOI：10.4236/oalib.1105817
语种：English
出版社：Scientific Research Pub
摘要：With the development of artificial intelligence, the automatic question answering technology has been paid more and more attention. Along with the technology’s maturing, the problem is gradually exposed. This technique has several major difficulties. There is semantic recognition. How accurate are the answers to the questions? Because Chinese grammar is relatively complex. There are many different ways of saying the same thing. There is a powerful challenge to semantic recognition. Due to poor semantic recognition, the accuracy of the corresponding questions and answers is low. Aiming at this kind of questions, we build a Q & A library for common use of cars. Firstly, TFIDF method is used to build a basic FAQ retrieval system. Then we use BILSTM-siamese network to construct a semantic similarity model. The accuracy rate on the test set was 99.52%. The final FAQ system: first retrieves 30 most similar questions using the TFIDF model, then uses BILSTM-siamese network matching and returns the answer of the most similar question. The system has a lot to be improved. For example, how to combine this system with speech recognition? How to realize speech recognition will be a great challenge.
关键词：TFIDFBILSTM-SiameseFAQ