论文标题
使用深神经网络的印尼语言检测 - 支持向量机器
Relation Detection for Indonesian Language using Deep Neural Network -- Support Vector Machine
论文作者
论文摘要
关系检测是确定两个实体是否相关的任务。在本文中，我们采用神经网络来对印尼语言的两个指定实体进行关系检测。我们使用了诸如单词嵌入，位置嵌入，POS-TAG嵌入和角色嵌入之类的功能。对于模型，我们将模型分为两个部分：前部分类器（卷积层或LSTM层）和后部分类器（密集层或SVM）。我们对神经网络超级参数和SVM进行了网格搜索方法。我们使用6000个印度尼西亚句子进行培训过程，1,125句进行测试。最好的结果是使用卷积层作为前部和SVM作为后部零件，在F1得分上为0.8083。
Relation Detection is a task to determine whether two entities are related or not. In this paper, we employ neural network to do relation detection between two named entities for Indonesian Language. We used feature such as word embedding, position embedding, POS-Tag embedding, and character embedding. For the model, we divide the model into two parts: Front-part classifier (Convolutional layer or LSTM layer) and Back-part classifier (Dense layer or SVM). We did grid search method of neural network hyper parameter and SVM. We used 6000 Indonesian sentences for training process and 1,125 for testing. The best result is 0.8083 on F1-Score using Convolutional Layer as front-part and SVM as back-part.
