对文本进行分类

定义可对文档中的文本进行分类的类别。

本主题描述如何对文本进行分类。 如果要对文档进行分类，请使用“内容挖掘”应用程序。 更多信息，请参阅 分类器类型。

添加文本分类器以将集合中的文档中的文本分配到类别中。Discovery 使用您提供的标签和文本示例来预测集合中文本的类别。

要创建文本分类器，请完成以下步骤：

1. 创建包含示例文本的 CSV 文件，后跟每行的类别标签。

   CSV 文件必须采用 UTF-8 编码格式，并且必须满足以下要求:

   • 格式必须是 text,label。 text 是示例文本，label 是类别名称。

     添加完整的句子作为文本条目。 请勿在 CSV 文件中包含任何空白行。

     如果您需要在 text 列中的句子应用多个标签，可以添加更多 label 列。 例如，text,label,label。

   • 文件必须至少有两列，且没有标题。

   • 为要定义的每个类别添加 10 个或多个条目。 每个类别所需的最小条目数为 3。 为每个类别提供的示例越多，分类器越能预测集合中其他内容的类别。

   以下示例是一个 CSV 文件，用于定义名为 facility_temperature 和 catering 的两个类别。 示例文本由来自会议出席者的反馈组成。

   The rooms were too cold.,facility_temperature
   Breakfast did not include gluten-free options.,catering
   The rooms were too warm.,facility_temperature
   I was very comfortable in the session rooms.,facility_temperature
   The awards dinner was delicious.,catering
   Coffee ran out during one of the breaks.,catering
   The temperature was not comfortable.,facility_temperature
   I was very happy with the selection at lunch.,catering
   It was nice that you provided tea and coffee. Tea drinkers are often ignored.,catering
   Can you turn up the air conditioning? I was very warm.,facility_temperature
   My teeth were chattering because I was so cold.,facility_temperature
   The speaker left the room to find someone to adjust the temperature.,facility_temperature
   Would you consider an all-vegan menu next year?,catering
   I would like lemonade and iced tea to be served during the breaks.,catering
   The lunch staff was excellent.,catering
   Appreciated the fresh blueberry muffins at breakfast.,catering
   The hotel staff adjusted the temperature in my session room as soon as I asked. Excellent service!,facility_temperature
   Every meal was delicious and there was something for everyone.,catering
   The seats under the skylights were not comfortable. Too hot.,facility_temperature
   I was comfortable everywhere in the conference center. I never needed my emergency sweater.,facility_temperature
   

2. 从“改进工具”面板的 Teach 域概念 部分，然后单击 文本分类器。

3. 单击上传。

4. 指定分类器的名称，然后选择 CSV 文件中使用的语言。

5. 单击 上载 以浏览先前创建的 CSV 文件。

6. 单击创建。

   将根据您提供的训练数据创建分类器扩充项。

7. 选择要在其中应用文本分类器扩充项的集合和字段，然后单击 应用。

以下示例显示了使用样本 CSV 文件作为其训练数据创建的扩充项如何对文档中的文本进行分类。 在输出中，分类器扩充项将 facility_temperature 标签应用于文档文本。 label 存储在 enriched_{field_name} 数组中的 classes 数组内。

{
  "enriched_text": [
    {
      "classes": [
        {
          "confidence": 0.999692440032959,
          "label": "facility_temperature"
        }
      ]
    }
  ],
  "text": [
    "I think more attendees would stay awake in the sessions if the rooms were colder."
  ]
}