This is a tutorial that explain Apache OpenNLP API in very simple way with series of examples & walks through code for all aspects of it. Every article will explain in easy terms different concepts of Apache OpenNLP & give example code for each of them.
Basic steps involved in Apache Open NLP program.
- Sample Data for training: Create sample data in certain format. This can be real historical data like review comments or different language words etc. This should be in a way which Apache OpenNLP can understand.
- Train a model: Using sample data, we train a model object. Model object is a set of learning which can be used by Apache OpenNLP algorithms.
- Process input data: Once we have model ready, we can then process & analyze input data with Apache OpenNLP tools to get output like language detection, document categorization etc.
Dependency for examples
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Go through below articles which explain each feature of Apache Open NLP in details & in easiest way possible.