A Review Paper On The Application Of Knowledge Graph On Various Service Providing Platforms.

Vanshika Vikas Nigam, Shreya Paul, A. Agrawal, Rishabh Bansal
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引用次数: 3

Abstract

During the past decade or so, knowledge graphs have stealthily made way into our daily lives, whether through voice assistants (the likes of Alexa, Google Assistant or Siri), spontaneous search results or customized personal shopping experiences through online stores recommenders. Today, we are surrounded and constantly interacting with knowledge graphs on a regular basis. The scope and impact of knowledge graphs and underlying graph databases are still a mystery to people. Considering its smooth entry into our lives, most of us are unaware of how dependent we actually are on the technology. In this paper, we have shown the working of the Google knowledge graph and how the knowledge graph works as the most effective recommendation system. We have discussed how it finds its way through daily life in various fields like Banking, Social media (Facebook, LinkedIn, Netflix), Food application (Uber Eats) and the Healthcare sector.
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知识图谱在各类服务提供平台上的应用综述
在过去十年左右的时间里,知识图谱已经悄悄进入了我们的日常生活,无论是通过语音助手(比如Alexa、谷歌助手或Siri)、自发的搜索结果,还是通过在线商店推荐来定制个人购物体验。今天,我们被知识图谱所包围,并经常与之互动。知识图和底层图数据库的范围和影响对人们来说仍然是一个谜。考虑到它顺利进入我们的生活,我们大多数人都没有意识到我们实际上是多么依赖这项技术。在本文中,我们展示了谷歌知识图谱的工作原理,以及知识图谱如何成为最有效的推荐系统。我们已经讨论了它如何在日常生活的各个领域,如银行、社交媒体(Facebook、LinkedIn、Netflix)、食品应用(Uber Eats)和医疗保健领域找到自己的方式。
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