Marilyn Choque-Díaz, Jimmy Armas-Aguirre, P. Shiguihara-Juárez
{"title":"认知技术模型与聊天机器人增强学术支持服务","authors":"Marilyn Choque-Díaz, Jimmy Armas-Aguirre, P. Shiguihara-Juárez","doi":"10.1109/INTERCON.2018.8526411","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a cognitive technology model to enhance academic support services with chatbots. The difference between the conventional models and the model proposed in this paper lies in adding Customer Experience patterns to the chatbot. This could substantially improve the interaction between the chatbot and the student in the institution. Our proposed model also emphasizes the use of best practices for real-time data processing. The model consists of five phases: 1. Capture; 2. Understanding Natural Language; 3. Dialog management; 4. Generated responses; 5. Consumption. We evaluate our cognitive technology model with undergraduate students at Universidad Peruana de Ciencias Aplicadas. The preliminary results showed a reduction of more than 99.9% in the average response time expected per query and an acceptance level of 80% within the target population.","PeriodicalId":305576,"journal":{"name":"2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Cognitive technology model to enhanced academic support services with chatbots\",\"authors\":\"Marilyn Choque-Díaz, Jimmy Armas-Aguirre, P. Shiguihara-Juárez\",\"doi\":\"10.1109/INTERCON.2018.8526411\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a cognitive technology model to enhance academic support services with chatbots. The difference between the conventional models and the model proposed in this paper lies in adding Customer Experience patterns to the chatbot. This could substantially improve the interaction between the chatbot and the student in the institution. Our proposed model also emphasizes the use of best practices for real-time data processing. The model consists of five phases: 1. Capture; 2. Understanding Natural Language; 3. Dialog management; 4. Generated responses; 5. Consumption. We evaluate our cognitive technology model with undergraduate students at Universidad Peruana de Ciencias Aplicadas. The preliminary results showed a reduction of more than 99.9% in the average response time expected per query and an acceptance level of 80% within the target population.\",\"PeriodicalId\":305576,\"journal\":{\"name\":\"2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INTERCON.2018.8526411\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTERCON.2018.8526411","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cognitive technology model to enhanced academic support services with chatbots
In this paper, we propose a cognitive technology model to enhance academic support services with chatbots. The difference between the conventional models and the model proposed in this paper lies in adding Customer Experience patterns to the chatbot. This could substantially improve the interaction between the chatbot and the student in the institution. Our proposed model also emphasizes the use of best practices for real-time data processing. The model consists of five phases: 1. Capture; 2. Understanding Natural Language; 3. Dialog management; 4. Generated responses; 5. Consumption. We evaluate our cognitive technology model with undergraduate students at Universidad Peruana de Ciencias Aplicadas. The preliminary results showed a reduction of more than 99.9% in the average response time expected per query and an acceptance level of 80% within the target population.