Batch processing of abstracts and automatic crawling of papers by keywords are two different features of ArXiv Paper Summarizer, and the main differences are as follows:
Batch processing of dissertation abstracts:
- Processing object: a list of specific papers explicitly known to the user
- Input method: text file containing multiple arXiv summary URLs
- Run command: python url_summarize.py -batch urls.txt
- Suitable scenario: multiple papers are known that need to be read and you want to get all the abstracts at once
Keyword auto-crawl:
- Processing object: unknown papers on arXiv that meet the keyword criteria
- Input method: set keywords and date range in configuration file
- Run the command: python keyword_summarize.py
- Suitable scenario: tracking the latest research progress in a specific field
- Additional advantage: can be set to run automatically on a daily basis, creating continuous updates
Simply put, batch processing is a case where the user already has a clear target paper, while keyword crawling is a case where the tool automatically discovers new papers and generates abstracts. The former ensures accuracy, the latter side rediscovery. The two functions can be used in combination - first use the keyword function to discover new papers, and then use the batch function to process the parts of interest.
This answer comes from the articleArXiv Paper Summarizer: automatic summary tool for arXiv papersThe
