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Analyzing the use of existing systems for the CLPsych 2019 Shared Task

机译:分析用于CLPSY3 2019共享任务的现有系统的使用

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In this paper we describe the UniOvi-WESO classification systems proposed for the 2019 Computational Linguistics and Clinical Psychology (CLPsych) Shared Task. We explore the use of two systems trained with ReachOut data from the 2016 CLPsych task, and compare them to a baseline system trained with the data provided for this task. All the classifiers were trained with features extracted just from the text of each post, without using any other metadata. We found out that the baseline system performs slightly better than the pre-trained systems, mainly due to the differences in labeling between the two tasks. However, they still work reasonably well and can detect if a user is at risk of suicide or not.
机译:本文介绍了2019年计算语言学和临床心理学(CLPSYCH)共享任务所提出的Uniovi-Weso分类系统。我们探讨了从2016 CLPSYCR任务中使用覆盖数据验证的两个系统的使用,并将它们与为此任务提供的数据进行培训的基线系统进行比较。所有分类器都培训,只能从每个帖子的文本中提取的功能培训,而不使用任何其他元数据。我们发现基线系统比预训练的系统略好,主要是由于两个任务之间标记的差异。然而,它们仍然合理地工作,可以检测用户是否有自杀的风险。

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