分析有争议的社交媒体社区

Igor Stupavský, V. Vranić
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引用次数: 1

摘要

我们可以通过在互联网上阅读非结构化的文本来了解我们所需要的关于世界的大部分信息。人工智能的作用就是理解这个文本并正确地理解它,对它进行分类,并做出正确的系统响应。世界上大多数国家都在使用英语等语言的文本,它们有自己训练有素的工具。这些模型在确定词性、句子结构等方面相当出色。如果我们想教人工智能识别少数民族语言,我们就会遇到一个问题。在我们的例子中,我们选择斯洛伐克语作为少数民族语言。在上一篇文章中,我们报告了可用工具对单词类型的错误识别。在本文中,我们显著提高了对第二位置单词的识别。我们计划继续开发斯洛伐克优化软件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysing the controversial social media community
We can learn most of the information we need about the world by reading unstructured text on the internet. The role of artificial intelligence is to understand this text and correctly understand it, categorize it, and make the correct system response. Texts in languages like English, which is spoken by most of the world, have their own trained tools. These models are fairly good at determining things like part of speech, sentence structure, and the like. If we want to teach artificial intelligence to recognize even minority languages, we run into a problem. In our case, we chose Slovak as the minority language. In the previous article, we reported on the misidentification of word types by the available tools. In this paper, we have significantly improved the identification of words in the second place. We plan to continue the development of Slovak-optimized software.
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