There are a few resumes that have some content that takes more time to process. See below how parsing happens and how it works.
1. Document analysis If we have PDF or scanned resumes, we have extra processing due to complex PDF programming file programming because our parser converts every resume document into a text form before parsing.
2. Second is parsing time; the system analyzes a complete resume via NLP and Deep learning; this is approximately 400 ms. And we can speed this with the help of filed configuration module by disabling non-required fields. You can disable the data fields that can cause bias, such as Candidate Image, Taxonomy, HTML Resume, etc. Since our AI analysis that we don't need to extract all fields, it will skip that section and considerably improve the parsing speed.
Generally, users disable - Candidate Image, Taxonomy, HTML Resume, Certifications, Publications, Template Output, and Category fields. But this will be your choice, and you can enable & disable it as per your need.
3. Taxonomies, you see RChilli provides many taxonomies. The time taken is based on how many job profiles or skills are written in the resume. If you are not using it, you can disable it using the configuration feature to get a better processing time.
4. Data transfer time, our servers are located in Dallas and Chicago. If you are testing this at the local computer, we have to add transfer time from your local machine to the server, And if you process it via server, then latency is just 1 to 2 ms. To get a better processing time, please try this from online servers like AWS, Google Suite, or Azure if you are trying this from the local computer.
If you still have a question, you can always contact RChilli Support by creating an RChilli Helpdesk ticket or simply by sending an email at email@example.com.
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