Noisy text analytics refers to the process of analyzing text data that contains various types of "noise." In this context, "noise" can include irrelevant information, errors, inconsistencies, informal language, slang, typos, or any other elements that might complicate the extraction of meaningful insights from the text. Key aspects of noisy text analytics include: 1. **Data Cleaning**: This involves preprocessing the text to remove or correct noisy elements.
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