A Semantic Knowledge Management System for Government Repositories

E. Tello-Leal, Ana B. Ríos-Alvarado, Alan Díaz-Manríquez
{"title":"A Semantic Knowledge Management System for Government Repositories","authors":"E. Tello-Leal, Ana B. Ríos-Alvarado, Alan Díaz-Manríquez","doi":"10.1109/DEXA.2015.48","DOIUrl":null,"url":null,"abstract":"Nowadays, in a knowledge-driven economy, the organizations, public or private, require to make an appropriate managing knowledge assets to sustain competitive edge in global markets or in governmental services. Advances in Information and Communications Technologies have supported innovations in Knowledge Management (KM). Since the KM has been recognized as one of the critical factors for obtaining organizational competitiveness. KM is among the promising areas for the application of Semantic Web. In this paper we propose an approach to the development of a technological platform for KM that integrates semantic Web technologies. This platform supports all processes required in knowledge management. Therefore, the platform enables the automatic identification of patterns and generation of the taxonomies from unstructured texts (documents). The platform consists of tools that allow storing documents (from a knowledge contributor interface), processing of source documents, i.e. identifying sentences, stop-words, identifying n-grams, and generating bags of words, denoting lexical patterns, taxonomic-relation extraction, and inference algorithms to retrieve knowledge from a set of repositories. These algorithms use the previous phases to retrieve knowledge more accurately derived from the semi-structured or structured information previously generated.","PeriodicalId":239815,"journal":{"name":"2015 26th International Workshop on Database and Expert Systems Applications (DEXA)","volume":"186 5 Suppl Nature 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 26th International Workshop on Database and Expert Systems Applications (DEXA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEXA.2015.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Nowadays, in a knowledge-driven economy, the organizations, public or private, require to make an appropriate managing knowledge assets to sustain competitive edge in global markets or in governmental services. Advances in Information and Communications Technologies have supported innovations in Knowledge Management (KM). Since the KM has been recognized as one of the critical factors for obtaining organizational competitiveness. KM is among the promising areas for the application of Semantic Web. In this paper we propose an approach to the development of a technological platform for KM that integrates semantic Web technologies. This platform supports all processes required in knowledge management. Therefore, the platform enables the automatic identification of patterns and generation of the taxonomies from unstructured texts (documents). The platform consists of tools that allow storing documents (from a knowledge contributor interface), processing of source documents, i.e. identifying sentences, stop-words, identifying n-grams, and generating bags of words, denoting lexical patterns, taxonomic-relation extraction, and inference algorithms to retrieve knowledge from a set of repositories. These algorithms use the previous phases to retrieve knowledge more accurately derived from the semi-structured or structured information previously generated.
面向政府知识库的语义知识管理系统
如今,在一个知识驱动的经济,组织,公共或私人,需要作出适当的管理知识资产,以保持在全球市场或政府服务的竞争优势。信息和通信技术的进步支持了知识管理(KM)的创新。由于知识管理已被公认为获得组织竞争力的关键因素之一。知识管理是语义网最有前途的应用领域之一。在本文中,我们提出了一种集成语义Web技术的知识管理技术平台的开发方法。该平台支持知识管理所需的所有流程。因此,该平台支持从非结构化文本(文档)自动识别模式和生成分类法。该平台由允许存储文档(来自知识贡献者界面)、处理源文档(即识别句子、停止词、识别n-gram)和生成单词包、表示词汇模式、分类关系提取和推理算法(从一组存储库检索知识)的工具组成。这些算法使用前面的阶段来更准确地检索从先前生成的半结构化或结构化信息中获得的知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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