[英]Sentiment Analysis instead of Positive Negative Neutral, I want to sentiment by category of products
Im doing a categorical product sentiment analysis.我正在做一个分类的产品情绪分析。 But I dont quite know what keyword to search for and what methods should I use.
但是我不太清楚要搜索什么关键字以及应该使用什么方法。 Im using this dataset for this https://huggingface.co/datasets/viewer/?dataset=amazon_reviews_multi&config=en Im doint a neural search project and my model would be the Review text and product category.
我将此数据集用于此https://huggingface.co/datasets/viewer/?dataset=amazon_reviews_multi&config=en我正在做一个神经搜索项目,我的模型将是评论文本和产品类别。
I think the keyword you are looking for is 'multi-task classification'.我认为您正在寻找的关键字是“多任务分类”。 Sometimes this is called 'joint learning', where a model learns how to solve two or more tasks simultaneously.
有时这被称为“联合学习”,模型学习如何同时解决两个或多个任务。
Task 1: Classify sentiment.任务 1:对情绪进行分类。 Task 2: Classify product category.
任务 2:分类产品类别。
It is possible to train one neural network model to learn how to classify both sentiment and category at the same time.可以训练一个神经网络模型来学习如何同时对情绪和类别进行分类。 You'll end up having an output layer with two groups of nodes, one for the first task, and one for the other.
您最终将拥有一个包含两组节点的输出层,一组用于第一个任务,一组用于另一组。 You need to define loss criteria for both groups, add them together, and use the combined loss to train the network.
您需要为这两个组定义损失标准,将它们加在一起,并使用组合损失来训练网络。
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