Application of AI in document processing

Anandarup Ghosh

• 1 min read
Application of AI in document processing

AI has found numerous applications in document processing, streamlining various tasks and enhancing efficiency.

Applications

  1. Optical Character Recognition (OCR): AI-powered OCR technology converts scanned or printed documents into editable and searchable text. It enables the extraction of text from images, PDFs, and handwritten documents, making them machine-readable and allowing for efficient indexing and analysis.
  2. Sentiment Analysis: AI-powered sentiment analysis helps organizations analyze customer feedback, social media posts, and other documents to determine the sentiment of the text. By automatically determining whether the sentiment is positive, negative, or neutral, organizations can gain valuable insights into customer satisfaction, brand perception, and market trends.
  3. Language Translation: NLP techniques enable AI systems to understand and process human language. NER(Named Entity Recognition) is a technique used to extract specific pieces of information from unstructured text, such as names, dates, locations, and organizations. It is commonly used to extract relevant information from documents such as news articles, legal documents, and medical records. Language translation is useful in applications such as document translation, website localization, and international communication.
  4. Document Classification: AI algorithms can categorize and classify documents based on their content, structure, or purpose. This helps in organizing large document repositories, enabling quick retrieval and efficient document management, and is particularly useful in industries such as legal, finance, and healthcare, where large volumes of documents need to be organized and sorted for quick retrieval and analysis.
  5. Text Summarization: AI-powered algorithms can generate concise summaries of lengthy documents, saving time and effort for readers. This is useful for tasks like document triage, information retrieval, and content analysis and is extensively used in scenarios where individuals need to review large amounts of information quickly, such as news articles, research papers, or legal documents.