Building a Knowledge Graph on Video Transcript Text Data

Bagas Triaji, W. Andriyani, B. Dp, Faizal Makhrus
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Abstract

Youtube is a video platform which not only provides entertainment but also education in which knowledge can be dug based on video transcripts. The results of this knowledge can be formed as a knowledge graph to build a knowledge base that saves storage space. Moreover, it can be used for other purposes such as recommendation systems and search engines. Prosen built a knowledge graph using NLP to extract the text by identifying the subject-verb-object (SVO) and stored in the graph database. The construction of a knowledge graph on a Youtube video transcript was successfully carried out. However, there are still obstacles in the process of extracting text using NLP which is less optimal so it is possible that there is still a lot of knowledge that has failed to be obtained.
基于视频文本数据的知识图谱构建
Youtube是一个既提供娱乐又提供教育的视频平台,可以通过视频文本挖掘知识。这些知识的结果可以形成知识图,从而建立知识库,节省存储空间。此外,它还可以用于其他目的,如推荐系统和搜索引擎。Prosen通过识别主谓宾关系(SVO),利用自然语言处理(NLP)构建知识图谱,提取文本并存储在图谱数据库中。成功地构建了Youtube视频文本的知识图谱。然而,在使用NLP提取文本的过程中仍然存在障碍,这不是最优的,所以仍然有可能有很多知识未能获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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