农业机械学报2018，Vol.49Issue(5)：271-276,6.DOI:10.6041/j.issn.1000-1298.2018.05.032
基于BIGRU的番茄病虫害问答系统问句分类研究
Question Classification of Tomato Pests and Diseases Question Answering System Based on BIGRU
摘要
Abstract
The notable feature of a question answering system is to understand the semantic information of the user's question.Question classification,as the key module of question answering system,plays a decisive role in the efficiency of system retrieval.In order to classify the user's questions,a classification model of tomato pests and diseases based on word2vec and bi-directional gated recurrent unit (BIGRU)was constructed.word2vec was used to transform the words in the sentence into the word vector with semantic information.The word vector was used as the initial corpus.Two neural network methods and a machine learning method were adopted to train the classification model.Totally 2000 tomato pests and diseases related questions were selected,which were divided into two categories:tomato diseases and tomato pests.The results showed that the classification accuracy,recall rate and F1 value by using the BIGRU model were 2 ～ 5 percentage points higher than those by using convolutional ceural network (CNN) and K-nearest neighbor (KNN) classification algorithm.Further experimental results comparison indicated that the BIGRU model performed the best on tomato pest and diseases question classification.The BIGRU model was simple in structure,less in model training parameters,and fast in training speed.It met the response time requirements of question answering system.关键词
番茄/病虫害/问答系统/问句分类/BIGRUKey words
tomato/pests and diseases/question answering system/question classification/BIGRU分类
信息技术与安全科学引用本文复制引用
赵明,董翠翠,董乔雪,陈瑛..基于BIGRU的番茄病虫害问答系统问句分类研究[J].农业机械学报,2018,49(5):271-276,6.基金项目
国家自然科学基金项目(61503386) （61503386）
