近似最近邻提取技术和神经网络在CLPsych 2022共享任务中的自杀风险预测

Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 1900-01-01 DOI:10.18653/v1/2022.clpsych-1.17

Hermenegildo Fabregat Marcos, Ander Cejudo, Juan Martínez-Romo, Alicia Pérez, Lourdes Araujo, Nuria Lebea, M. Oronoz, Arantza Casillas

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引用次数: 3

摘要

本文描述了我们小组参与CLPsych 2022共享任务的情况。对于任务A，它试图捕捉情绪随时间的变化，我们应用了一种近似近邻(ANN)提取技术，目的是根据用户消息的接近程度，基于这些消息在向量空间中的表示，重新标记用户消息。对于子任务B，我们使用子任务A的输出来训练一个递归神经网络(RNN)来预测用户层面的自杀风险。考虑到我们的团队是少数几个利用组织者提出的虚拟环境并利用任务A输出来预测任务B结果的团队之一，所获得的结果非常有竞争力。

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Approximate Nearest Neighbour Extraction Techniques and Neural Networks for Suicide Risk Prediction in the CLPsych 2022 Shared Task

This paper describes the participation of our group on the CLPsych 2022 shared task.For task A, which tries to capture changes in mood over time, we have applied an Approximate Nearest Neighbour (ANN) extraction technique with the aim of relabelling the user messages according to their proximity, based on the representation of these messages in a vector space. Regarding the subtask B, we have used the output of the subtask A to train a Recurrent Neural Network (RNN) to predict the risk of suicide at the user level.The results obtained are very competitive considering that our team was one of the few that made use of the organisers’ proposed virtual environment and also made use of the Task A output to predict the Task B results.

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Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology

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