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2. NotebookLM - Wikipedia

   en.wikipedia.org/wiki/NotebookLM

   [2] [5] Google describes it as a "virtual research assistant". [6] In addition to text files, NotebookLM can process PDFs, Google Docs, websites, and Google Slides. [1] The "Audio Overviews" feature, [7] released in September 2024, gained media attention for its ability to condense complex documents into podcast-style audio files.

3. PDF - Wikipedia

   en.wikipedia.org/wiki/PDF

   Text in PDF is represented by text elements in page content streams. A text element specifies that characters should be drawn at certain positions. The characters are specified using the encoding of a selected font resource. A font object in PDF is a description of a digital typeface.

4. Google Docs - Wikipedia

   en.wikipedia.org/wiki/Google_Docs

   Google Docs is an online word processor and part of the free, web-based Google Docs Editors suite offered by Google. Google Docs is accessible via a web browser as a web-based application and is also available as a mobile app on Android and iOS and as a desktop application on Google's ChromeOS .

5. List of PDF software - Wikipedia

   en.wikipedia.org/wiki/List_of_PDF_software

   A PDF creator and virtual PDF printer for Microsoft Windows PDF-XChange: Proprietary: Yes: PDF Tools allows creation of PDFs from many types of source input (images, scans, etc.). The PDF-XChange print driver allows printing directly to a PDF. A "lite" version of the print driver is free for non-commercial (home and academic) use. PrimoPDF ...

6. Google Notebook - Wikipedia

   en.wikipedia.org/wiki/Google_Notebook

   Google Notebook was a free online application offered by Google that allowed users to save and organize clips of information while conducting research online. The browser-based tool permitted a user to write notes, clip text and images, and save links from pages during a browser session.

7. Automatic summarization - Wikipedia

   en.wikipedia.org/wiki/Automatic_summarization

   Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.