Text mining
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Text mining is a process that derives meaningful information from text through techniques of artificial intelligence such as turning text into numbers. It involves preprocessing text through steps like cleanup and tokenization, transforming text using methods like bag-of-words and vector space models, selecting features, applying data mining techniques, and evaluating the output. Text mining has applications in areas like web mining, medical fields, and resume filtering by automatically analyzing texts from open-ended surveys, warranty claims, interviews, and competitor websites.
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Text mining
- 2. Introduction Of Text Mining ● Process of deriving Meaningful Information from text. ● Also known as Text Data Mining. ● Technology of AI. ● “Turn text into numbers”.
- 4. Areas Of Text Mining
- 6. 1. Text-pre Processing ● Text clean up. ● Tokenization. ● Part of speech tagging. 1. Text Transformation ● Bag Of words. ● Vector Space. 1. Feature Selection 2. Data Mining 3. Evaluation
- 7. 6. Applications ● Web-mining. ● Medical. ● Resume Filtering etc.
- 8. Application Of Text Mining 01 Analysing Open-ended-survey responses. 03 Analysing Warranty Or insurance,claims,diagnosis,interviews,etc. 04 Investigating Competitors by crawling their websites. 02 Automatic Processing of Message,Email,etc.
- 9. Pros And Cons Of Data Mining
- 10. Thank You.