{"title":"简单问题转换模板模式","authors":"Rakhmayudhi, W. Suwarningsih","doi":"10.1109/IC2IE50715.2020.9274666","DOIUrl":null,"url":null,"abstract":"The classification of question types in the Indonesian medical domain is the important component of the medical question answering system. The strategy proposed in this paper is to build the template pattern and rule-based parser for extracting some important words using the generated feature to automatically query the classification of question. Classification aims to prove that the system is capable of classifying queries only by using the available language resources. The proposed method has been evaluated using datasets collected from various Indonesian health consultation websites. Test results from the proposed method indicated that the classification process is very effective with an accuracy of 84.33%.","PeriodicalId":211983,"journal":{"name":"2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Template Pattern for Simple Question Transformation\",\"authors\":\"Rakhmayudhi, W. Suwarningsih\",\"doi\":\"10.1109/IC2IE50715.2020.9274666\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The classification of question types in the Indonesian medical domain is the important component of the medical question answering system. The strategy proposed in this paper is to build the template pattern and rule-based parser for extracting some important words using the generated feature to automatically query the classification of question. Classification aims to prove that the system is capable of classifying queries only by using the available language resources. The proposed method has been evaluated using datasets collected from various Indonesian health consultation websites. Test results from the proposed method indicated that the classification process is very effective with an accuracy of 84.33%.\",\"PeriodicalId\":211983,\"journal\":{\"name\":\"2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC2IE50715.2020.9274666\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC2IE50715.2020.9274666","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Template Pattern for Simple Question Transformation
The classification of question types in the Indonesian medical domain is the important component of the medical question answering system. The strategy proposed in this paper is to build the template pattern and rule-based parser for extracting some important words using the generated feature to automatically query the classification of question. Classification aims to prove that the system is capable of classifying queries only by using the available language resources. The proposed method has been evaluated using datasets collected from various Indonesian health consultation websites. Test results from the proposed method indicated that the classification process is very effective with an accuracy of 84.33%.