Skip to content

Latest commit

 

History

History
42 lines (30 loc) · 2.29 KB

README.md

File metadata and controls

42 lines (30 loc) · 2.29 KB
Raw

deep-business

AI for Business is Now, and the Future.

deep-business utilizes ChatGPT to summarize and chat with business papers, helping researchers stay up-to-date with the latest research trends. If you find this project useful, please give it a star!

The project is built on ChatPaper, and adds parse templates for business papers, which enables a more precise extraction of paper structure and content, as well as providing more insightful chat answers.

Highlights

  • PDF Parse Templates Designed for Business Journals. We design specialized PDF parsing templates for top business journals. A more targeted answer is generated on a more accurate and clean chapter structure and corresponding text.
  • Quick Summary. Use the built-in prompt to summarize the paper. Get the main points in 5 minutes!
  • Auto-Reference in User Chat. Use <chapter number> in your questions to quickly reference the corresponding chapter content and get a more focused answer.

Support Journals

Note that you must use the official version of the paper downloaded from the journal's website to make the built-in parse templates take effect. The supported journals and their jcode (abbreviation)

  • mnsc: Management Science
  • isre: Information Systems Research
  • misq: MIS Quarterly
  • mksc: Marketing Science
  • opre: Operations Research
  • jf: Journal of Finance
  • jfe: Journal of Financial Economics
  • rfs: Review of Financial Studies

Quickly Start

Open In Colab to summarize paper "Machine Learning vs. Economic Restrictions: Evidence from Stock Return Predictability"

Get Connected

If you encountered any problem / have some suggestions / want to contribute for this project, feel free to open an issue.

  • Slack
  • WeChat Official Account (In Chinese):