{"title":"基于引文的DEA从专利文本数据中选择核心词","authors":"Shigeaki Onoda, K. Okuhara","doi":"10.1109/ICAIIC.2019.8668999","DOIUrl":null,"url":null,"abstract":"The web includes enormous data such as patents. The purpose of this research finds the rule of textual patent data and creates new model. Hence, we suggest new weighted method using DEA to handle unstructured data like patent. Our proposed method is advantageous because this considers the value of the patent compared with TF-IDF and other weighted methods. Using suggested method, we probe new text-mining in the field of patent.","PeriodicalId":273383,"journal":{"name":"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Selection of Core Words from Textual Patent Data with DEA based on Citation\",\"authors\":\"Shigeaki Onoda, K. Okuhara\",\"doi\":\"10.1109/ICAIIC.2019.8668999\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The web includes enormous data such as patents. The purpose of this research finds the rule of textual patent data and creates new model. Hence, we suggest new weighted method using DEA to handle unstructured data like patent. Our proposed method is advantageous because this considers the value of the patent compared with TF-IDF and other weighted methods. Using suggested method, we probe new text-mining in the field of patent.\",\"PeriodicalId\":273383,\"journal\":{\"name\":\"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAIIC.2019.8668999\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIIC.2019.8668999","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Selection of Core Words from Textual Patent Data with DEA based on Citation
The web includes enormous data such as patents. The purpose of this research finds the rule of textual patent data and creates new model. Hence, we suggest new weighted method using DEA to handle unstructured data like patent. Our proposed method is advantageous because this considers the value of the patent compared with TF-IDF and other weighted methods. Using suggested method, we probe new text-mining in the field of patent.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
