{"title":"使用本体标记文档","authors":"Naoya Okumura, T. Miura","doi":"10.1109/ICDIPC.2015.7323016","DOIUrl":null,"url":null,"abstract":"Recently we can get to huge amount of complex information easily and quickly from internet. But it is hard to capture appropriate information inside since we should go through them and see quickly what's going on. So automatic summarization is indispensable. In this work, assuming concept hierarchy, we extract suitable labels for documents by abstracting and ranking characteristic words.","PeriodicalId":339685,"journal":{"name":"2015 Fifth International Conference on Digital Information Processing and Communications (ICDIPC)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Labelling document using ontology\",\"authors\":\"Naoya Okumura, T. Miura\",\"doi\":\"10.1109/ICDIPC.2015.7323016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently we can get to huge amount of complex information easily and quickly from internet. But it is hard to capture appropriate information inside since we should go through them and see quickly what's going on. So automatic summarization is indispensable. In this work, assuming concept hierarchy, we extract suitable labels for documents by abstracting and ranking characteristic words.\",\"PeriodicalId\":339685,\"journal\":{\"name\":\"2015 Fifth International Conference on Digital Information Processing and Communications (ICDIPC)\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Fifth International Conference on Digital Information Processing and Communications (ICDIPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDIPC.2015.7323016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Fifth International Conference on Digital Information Processing and Communications (ICDIPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDIPC.2015.7323016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recently we can get to huge amount of complex information easily and quickly from internet. But it is hard to capture appropriate information inside since we should go through them and see quickly what's going on. So automatic summarization is indispensable. In this work, assuming concept hierarchy, we extract suitable labels for documents by abstracting and ranking characteristic words.