Text processing is a fundamental aspect of data manipulation and analysis. It involves various techniques to extract, transform, and analyze text data. Here are some key concepts and techniques in text processing:

  • Text Extraction: Extracting text from different sources like documents, images, or web pages.
  • Text Cleaning: Removing unnecessary characters, stop words, and punctuation to improve the quality of the text.
  • Text Transformation: Converting text into a format suitable for further analysis, such as converting to lowercase, stemming, or lemmatization.
  • Text Analysis: Analyzing the text to extract insights, such as sentiment analysis, topic modeling, or named entity recognition.

For more information on text processing techniques, you can visit our Text Processing Techniques page.

Common Text Processing Tasks

  • Sentiment Analysis: Determining the sentiment of a text, whether it's positive, negative, or neutral.
  • Topic Modeling: Identifying the main topics in a collection of documents.
  • Named Entity Recognition: Identifying and classifying named entities in text, such as people, places, and organizations.

Text Processing Example

Resources