Natural language is what we use for communication. Techniques for processing such data to understand underlying meaning is collectively called as Natural Language Processing (NLP). The data could be speech, text or even an image and approach involve applying Machine Learning (ML) techniques on data to build applications involving classification, extracting structure, summarizing and translating data.
Text Mining vs Natural Language Processing Comparison Table
|Basis Of Comparison||Text mining||NLP|
|Goal||Extract high-quality information
from unstructured and structured text.Information could be patterned
in text or matching structure but the semantics in the text is not considered.
|Trying to understand what is conveyed in natural language by human- may text or speech. Semantic and grammatical structures are analyzed.|
|Outcome||Explanation of text using statistical indicators like
||Understanding what conveyed through text or speech like
|System Accuracy||Performance measure is direct and relatively simple.Here we have clearly measurable mathematical concepts. Measures can be automated||Highly difficult to measure system accuracy for machines.Human intervention is needed most of the time.For example, consider an NLP system, which translates from English to Hindi.Automate the measure of how accurately|
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