{"title":"模糊本体中的概念默认值","authors":"Julia Taylor Rayz, V. Raskin","doi":"10.1109/NAFIPS.2016.7851606","DOIUrl":null,"url":null,"abstract":"The paper explores the fuzzy status of implicit information in natural language text, focusing on conceptual defaults, the routinely omitted information that readers/hearers equally routinely reconstruct. Making this information available to the natural language processing computer is essential, and fuzziness is a major issue. An analysis of 1,000 English sentences has demonstrated a diverse combination of circumstances for detecting and computing defaults with their membership function values.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Conceptual defaults in fuzzy ontology\",\"authors\":\"Julia Taylor Rayz, V. Raskin\",\"doi\":\"10.1109/NAFIPS.2016.7851606\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper explores the fuzzy status of implicit information in natural language text, focusing on conceptual defaults, the routinely omitted information that readers/hearers equally routinely reconstruct. Making this information available to the natural language processing computer is essential, and fuzziness is a major issue. An analysis of 1,000 English sentences has demonstrated a diverse combination of circumstances for detecting and computing defaults with their membership function values.\",\"PeriodicalId\":208265,\"journal\":{\"name\":\"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)\",\"volume\":\"129 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2016.7851606\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2016.7851606","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The paper explores the fuzzy status of implicit information in natural language text, focusing on conceptual defaults, the routinely omitted information that readers/hearers equally routinely reconstruct. Making this information available to the natural language processing computer is essential, and fuzziness is a major issue. An analysis of 1,000 English sentences has demonstrated a diverse combination of circumstances for detecting and computing defaults with their membership function values.
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