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Is there a way to identify similar words and convert it into one word before match against training model using Stanford NLP library?

For example, user inputs could be:

  1. DashPro
  2. Dash Pro
  3. dpo
  4. Dash

For all the above inputs, the return result should be "DashPro" so that it can match with the training model which contains only "DashPro"

Which of NLP Stanford Library pipeline or tools can help to resolve above scenario. And if you can provide any example code or references using java?

Thanks,

Is there a way to identify similar words and convert it into one word before match against training model using Stanford NLP library?

For example, user inputs could be:

  1. DashPro
  2. Dash Pro
  3. dpo
  4. Dash

For all the above inputs, the return result should be "DashPro" so that it can match with the training model which contains only "DashPro"

Which of NLP Stanford Library pipeline or tools can help to resolve above scenario. And if you can provide any example code or references using java?

Thanks,

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