File:Rdf-graph2.png · Wikimedia Commons · See Wikimedia Commons
Also known as SemWeb, Sem Web, semantic web, Semantic Web Technologies
给万维网上的文档添加能被计算机所理解的语义
In the Vinony graph
Within Vinony's link graph, 语义网 is referenced by 681 other articles, and connects out to metadata, linked data and HTML.
It is catalogued under topics including Internet ages, Knowledge engineering and Semantic Web.
Its subject is documented across 45 Wikipedia language editions.
Research
2,481 papers- Semantic Web Technologies for Sharing Clinical Information in Health Care Systems.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2019
- Semantic Web in Healthcare: A Systematic Literature Review of Application, Research Gap, and Future Research Avenues.International journal of clinical practice · 2022
- A semantic web technology index.Scientific reports · 2022
- Semantic Web technologies for the big data in life sciences.Bioscience trends · 2014
- The semantic web in translational medicine: current applications and future directions.Briefings in bioinformatics · 2015
via PubMed
Wikidata facts
- Instance of
- software framework
- Subclass of
- Semantic integration
- Has part
- EuroVoc
- Official website
- www.w3.org/standards/semanticweb
- Image
- Rdf-graph2.png
Show 10 more facts
- short name
- Semantic Web
- studied by
- knowledge engineering
- discoverer or inventor
- Tim Berners-Lee
- Commons category
- Semantic Web
- topic's main category
- Category:Semantic Web
- topic has template
- Template:Semantic Web
- uses
- SPARQL
- has characteristic
- linked data
- Stack Exchange tag
- stackoverflow.com/tags/semantic-web
- P13411
- Mont Blanc
Sources (4)
via Wikidata · CC0
Article · 中文
语义网(英语:Semantic Web)是由万维网联盟的蒂姆·伯纳斯-李(Tim Berners-Lee)在1998年提出的一个概念,它的核心是:通过给万维网上的文档(如: HTML文档)添加能够被计算机所理解的语义(元数据),从而使整个互联网成为一个通用的信息交换媒介。语义万维网通过使用标准、置标语言和相关的处理工具来扩展万维网的能力。不过语意网概念实际上是基于很多已有技术的,也依赖于后来和text-and-markup与知识表现的综合。 "语义"网是由比现今成熟的网际搜索工具更加行之有效的、更加广泛意义的并且自动聚集和搜集信息的文档组成的。其最基本的元素就是。
Abstract from DBpedia / Wikipedia · CC BY-SA