整合本体论和语言学知识,用于概念信息提取

Roberto Basili, Michele Vindigni, Fabio Massimo Zanzotto
{"title":"整合本体论和语言学知识,用于概念信息提取","authors":"Roberto Basili, Michele Vindigni, Fabio Massimo Zanzotto","doi":"10.1109/WI.2003.1241190","DOIUrl":null,"url":null,"abstract":"Text understanding makes strong assumptions about the conceptualisation of the underlying knowledge domain. This mediates between the accomplishment of the specific task at the one hand and the knowledge expressed in the target text fragments at the other. However, building domain conceptualisations from scratch is a very complex and time-consuming task. Traditionally, the reuse of available domain resources, although not constituting always the best, has been applied as an accurate and cost effective solution. Here, we investigate the possibility of exploiting sources of domain knowledge (e.g. a subject reference system) to build a linguistically motivated domain concept hierarchy. The limitation connected with the use of domain taxonomies as ontological resources will be firstly discussed in the specific light of IE, i.e. for supporting linguistic inference. We then define a method for integrating the taxonomical domain knowledge and a general-purpose lexical knowledge base, like WordNet. A case study, i.e. the integration of the MeSH, Medical Subject Headings, and WordNet, will be then presented as a proof of the effectiveness and accuracy of the overall approach.","PeriodicalId":403574,"journal":{"name":"Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Integrating ontological and linguistic knowledge for conceptual information extraction\",\"authors\":\"Roberto Basili, Michele Vindigni, Fabio Massimo Zanzotto\",\"doi\":\"10.1109/WI.2003.1241190\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Text understanding makes strong assumptions about the conceptualisation of the underlying knowledge domain. This mediates between the accomplishment of the specific task at the one hand and the knowledge expressed in the target text fragments at the other. However, building domain conceptualisations from scratch is a very complex and time-consuming task. Traditionally, the reuse of available domain resources, although not constituting always the best, has been applied as an accurate and cost effective solution. Here, we investigate the possibility of exploiting sources of domain knowledge (e.g. a subject reference system) to build a linguistically motivated domain concept hierarchy. The limitation connected with the use of domain taxonomies as ontological resources will be firstly discussed in the specific light of IE, i.e. for supporting linguistic inference. We then define a method for integrating the taxonomical domain knowledge and a general-purpose lexical knowledge base, like WordNet. A case study, i.e. the integration of the MeSH, Medical Subject Headings, and WordNet, will be then presented as a proof of the effectiveness and accuracy of the overall approach.\",\"PeriodicalId\":403574,\"journal\":{\"name\":\"Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WI.2003.1241190\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI.2003.1241190","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24

摘要

文本理解对基础知识领域的概念化做出了强有力的假设。这在特定任务的完成和目标文本片段中表达的知识之间起到了中介作用。然而,从头开始构建领域概念化是一项非常复杂且耗时的任务。传统上,可用领域资源的重用虽然并不总是最好的,但已经作为一种准确且经济有效的解决方案被应用。在这里,我们探讨了利用领域知识来源(如主题参考系统)来构建语言动机领域概念层次的可能性。与使用领域分类法作为本体论资源有关的限制将首先在IE的特定角度进行讨论,即支持语言推理。然后,我们定义了一种方法,用于集成分类学领域知识和通用词汇知识库(如WordNet)。然后将提出一个案例研究,即整合MeSH、医学主题词和WordNet,以证明整体方法的有效性和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating ontological and linguistic knowledge for conceptual information extraction
Text understanding makes strong assumptions about the conceptualisation of the underlying knowledge domain. This mediates between the accomplishment of the specific task at the one hand and the knowledge expressed in the target text fragments at the other. However, building domain conceptualisations from scratch is a very complex and time-consuming task. Traditionally, the reuse of available domain resources, although not constituting always the best, has been applied as an accurate and cost effective solution. Here, we investigate the possibility of exploiting sources of domain knowledge (e.g. a subject reference system) to build a linguistically motivated domain concept hierarchy. The limitation connected with the use of domain taxonomies as ontological resources will be firstly discussed in the specific light of IE, i.e. for supporting linguistic inference. We then define a method for integrating the taxonomical domain knowledge and a general-purpose lexical knowledge base, like WordNet. A case study, i.e. the integration of the MeSH, Medical Subject Headings, and WordNet, will be then presented as a proof of the effectiveness and accuracy of the overall approach.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信