NLP with Java---Overview-优快云博客

本文链接：https://blog.youkuaiyun.com/qq_33938256/article/details/52763423

本文概述了自然语言处理中的关键任务，包括文本处理任务、理解NLP模型、数据准备等。详细介绍了从文本分割到实体识别的过程，并探讨了模型选择、训练及验证的基本步骤。

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Overview of text processing tasks

Finding Parts of Text–>split/tokenization
Finding Sentences–>Sentence Boundary Disambiguation (SBD)
- Finding People and Things–>Name Entity Recognition
- Detecting Parts of Speech–>POS Tagging
Classification(with label)/Clustering(without label)
Extracting Relationships–>IR
Combined Approaches

Split/Tokenization-->Sentence(SBD)-->NER-->POS-->Classification/Cluster-->IR

The basic steps include:

Identifying the task
Select a model
- Understanding the problem domain and
  the required quality of results permits us to select the appropriate model
Building and trainning the model
- Training a model is the process of executing an algorithm against a set of data, formulating the model, and then verifying the model
- labeled samples or dataset is called a corpus
Verifying the model
- split sample and test sets
- Often, only part of a corpus is used for training
  while the other part is used for verification
Using the model