{"title":"基于强化学习的CSMA/CA MAC协议性能增强","authors":"김태욱, Hwang Gyung-Ho","doi":"10.6109/JICCE.2021.19.1.1","DOIUrl":null,"url":null,"abstract":"Herein, we propose a document analysis system that analyzes papers or reports transformed into XML(Extensible Markup Language) format. It reads the document specified by the user, extracts keywords from the document, and compares the frequency of keywords to extract the top-three keywords. It maintains the order of the paragraphs containing the keywords and removes duplicated paragraphs. The frequency of the top-three keywords in the extracted paragraphs is re-verified, and the paragraphs are partitioned into 10 sections. Subsequently, the importance of the relevant areas is calculated and compared. By notifying the user of areas with the highest frequency and areas with higher importance than the average frequency, the user can read only the main content without reading all the contents. In addition, the number of paragraphs extracted through the deep learning model and the number of paragraphs in a section of high importance are predicted.","PeriodicalId":37530,"journal":{"name":"Journal of Information and Communication Convergence Engineering","volume":"19 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Performance Enhancement of CSMA/CA MAC Protocol Based on Reinforcement Learning\",\"authors\":\"김태욱, Hwang Gyung-Ho\",\"doi\":\"10.6109/JICCE.2021.19.1.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Herein, we propose a document analysis system that analyzes papers or reports transformed into XML(Extensible Markup Language) format. It reads the document specified by the user, extracts keywords from the document, and compares the frequency of keywords to extract the top-three keywords. It maintains the order of the paragraphs containing the keywords and removes duplicated paragraphs. The frequency of the top-three keywords in the extracted paragraphs is re-verified, and the paragraphs are partitioned into 10 sections. Subsequently, the importance of the relevant areas is calculated and compared. By notifying the user of areas with the highest frequency and areas with higher importance than the average frequency, the user can read only the main content without reading all the contents. In addition, the number of paragraphs extracted through the deep learning model and the number of paragraphs in a section of high importance are predicted.\",\"PeriodicalId\":37530,\"journal\":{\"name\":\"Journal of Information and Communication Convergence Engineering\",\"volume\":\"19 1\",\"pages\":\"1-7\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Information and Communication Convergence Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.6109/JICCE.2021.19.1.1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information and Communication Convergence Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.6109/JICCE.2021.19.1.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
Performance Enhancement of CSMA/CA MAC Protocol Based on Reinforcement Learning
Herein, we propose a document analysis system that analyzes papers or reports transformed into XML(Extensible Markup Language) format. It reads the document specified by the user, extracts keywords from the document, and compares the frequency of keywords to extract the top-three keywords. It maintains the order of the paragraphs containing the keywords and removes duplicated paragraphs. The frequency of the top-three keywords in the extracted paragraphs is re-verified, and the paragraphs are partitioned into 10 sections. Subsequently, the importance of the relevant areas is calculated and compared. By notifying the user of areas with the highest frequency and areas with higher importance than the average frequency, the user can read only the main content without reading all the contents. In addition, the number of paragraphs extracted through the deep learning model and the number of paragraphs in a section of high importance are predicted.
期刊介绍:
Journal of Information and Communication Convergence Engineering (J. Inf. Commun. Converg. Eng., JICCE) is an official English journal of the Korea Institute of Information and Communication Engineering (KIICE). It is an international, peer reviewed, and open access journal that is published quarterly in March, June, September, and December. Its objective is to provide rapid publications of original and significant contributions and it covers all areas related to information and communication convergence engineering including the following areas: communication system and applications, networking and services, intelligent information system, multimedia and digital convergence, semiconductors and communication devices, imaging and biomedical engineering, and computer vision and autonomous vehicles.