{"title":"一种从文本资源中发现语义特征的方法","authors":"C. Vicient, D. Sánchez, Antonio Moreno","doi":"10.1109/SMAP.2011.13","DOIUrl":null,"url":null,"abstract":"Data analysis algorithms focused on processing textual data rely on the extraction of relevant features from text and the appropriate association to their formal semantics. In this paper, a method to assist this task, annotating extracted textual features with concepts from a background ontology, is presented. The method is automatic and unsupervised and it has been designed in a generic way, so it can be applied to textual resources ranging from plain text to semi-structured resources (like Wikipedia articles). The system has been tested with tourist destinations and Wikipedia articles showing promising results.","PeriodicalId":346975,"journal":{"name":"2011 Sixth International Workshop on Semantic Media Adaptation and Personalization","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Methodology to Discover Semantic Features from Textual Resources\",\"authors\":\"C. Vicient, D. Sánchez, Antonio Moreno\",\"doi\":\"10.1109/SMAP.2011.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data analysis algorithms focused on processing textual data rely on the extraction of relevant features from text and the appropriate association to their formal semantics. In this paper, a method to assist this task, annotating extracted textual features with concepts from a background ontology, is presented. The method is automatic and unsupervised and it has been designed in a generic way, so it can be applied to textual resources ranging from plain text to semi-structured resources (like Wikipedia articles). The system has been tested with tourist destinations and Wikipedia articles showing promising results.\",\"PeriodicalId\":346975,\"journal\":{\"name\":\"2011 Sixth International Workshop on Semantic Media Adaptation and Personalization\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Sixth International Workshop on Semantic Media Adaptation and Personalization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMAP.2011.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Sixth International Workshop on Semantic Media Adaptation and Personalization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMAP.2011.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Methodology to Discover Semantic Features from Textual Resources
Data analysis algorithms focused on processing textual data rely on the extraction of relevant features from text and the appropriate association to their formal semantics. In this paper, a method to assist this task, annotating extracted textual features with concepts from a background ontology, is presented. The method is automatic and unsupervised and it has been designed in a generic way, so it can be applied to textual resources ranging from plain text to semi-structured resources (like Wikipedia articles). The system has been tested with tourist destinations and Wikipedia articles showing promising results.
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