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  • 标题:DAOLOT: A Semantic Browser
  • 本地全文:下载
  • 作者:Jo{~a}o Bruno Silva ; Andr Santos ; Jos Paulo Leal
  • 期刊名称:OASIcs : OpenAccess Series in Informatics
  • 电子版ISSN:2190-6807
  • 出版年度:2020
  • 卷号:83
  • 页码:5:1-5:11
  • DOI:10.4230/OASIcs.SLATE.2020.5
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:The goal of the Semantic Web is to allow the software agents around us and AIs to extract information from the Internet as easily as humans do. This semantic web is a network of connected graphs, where relations between concepts and entities make up a layout that is very easy for machines to navigate. At the moment, there are only a few tools that enable humans to navigate this new layer of the Internet, and those that exist are for the most part very specialized tools that require from the user a lot of pre-existing knowledge about the technologies behind this structure. In this article we report on the development of DAOLOT, a search engine that allows users with no previous knowledge of the semantic web to take full advantage of its information network. This paper presents its design, the algorithm behind it and the results of the validation testing conducted with users. The results of our validation testing show that DAOLOT is useful and intuitive to users, even those without any previous knowledge of the field, and provides curated information from multiple sources instantly about any topic.
  • 关键词:Semantic; Web; Named Entities; Search; SPARQL; RDF; COMUNICA
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