论文标题
解析泰国社会数据：泰国NLP的新挑战
Parsing Thai Social Data: A New Challenge for Thai NLP
论文作者
论文摘要
依赖性解析（DP）是一项任务，可以分析文本的句法结构和单词之间的关系。 DP被广泛用于改善自然语言处理（NLP）应用，以许多语言（例如英语）。 DP上的先前作品通常适用于正式书面语言。但是，它们不适用于非正式语言，例如社交网络中使用的语言。因此，必须通过此类社交网络数据对DP进行研究和探索。在本文中，我们探索并确定适合泰国社交网络数据的DP模型。之后，我们将确定适当的语言单元作为输入。结果表明，基于过渡的模型称为“改善肘部依赖性解析器”，其其他UAS的占优于81.42％。
Dependency parsing (DP) is a task that analyzes text for syntactic structure and relationship between words. DP is widely used to improve natural language processing (NLP) applications in many languages such as English. Previous works on DP are generally applicable to formally written languages. However, they do not apply to informal languages such as the ones used in social networks. Therefore, DP has to be researched and explored with such social network data. In this paper, we explore and identify a DP model that is suitable for Thai social network data. After that, we will identify the appropriate linguistic unit as an input. The result showed that, the transition based model called, improve Elkared dependency parser outperform the others at UAS of 81.42%.
