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This invention describes a computer program that cleans up messy or incomplete text in documents. It first removes or replaces the 'dirty' parts, sometimes in two steps: a general cleanup, then a more specific one tailored to the document's topic. After cleaning, the program analyzes the text, identifies the most important sentences, and then uses those to create a summary of the document's content.
Why it matters: Filed before the widespread adoption of advanced machine learning and large language models, the core tasks of identifying and cleaning 'dirty text' and generating summaries from documents are now significantly more effective and accessible. Modern NLP tools and LLMs can perform these operations with greater accuracy and less manual rule-setting than was possible in 2001.
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