Punctuation Removal
Explore the process of punctuation removal and its impact on text preprocessing. Understand the benefits of removing punctuation for consistency, precise tokenization, and reducing features in machine learning. Discover when retaining punctuation is essential, such as for sentiment analysis or information extraction, helping you make informed preprocessing decisions.
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Introduction
Punctuation removal is the process of removing punctuation marks from text data. Examples of such punctuation marks include periods (.), commas (,), question marks (?), exclamation marks (!), colons (:), semicolons (;), quotation marks (“ ”), parentheses (()), brackets ([]), and hyphens and dashes (-, –, —). Removing such marks produces a text representation that’s less cluttered and more focused on the text’s main ideas, which can improve efforts during data analysis and modeling. ...