Which data cleansing method involves correcting misspellings, typos, and grammatical errors in textual data?
- Data deduplication
- Data imputation
- Data standardization
- Text normalization
Text normalization is a data cleansing method that involves correcting misspellings, typos, and grammatical errors in textual data to ensure consistency and accuracy. It may include tasks like converting text to lowercase, removing punctuation, and expanding abbreviations to their full forms, making the data more suitable for analysis and processing.
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