https://github.com/jalajthanaki/basic_job_recommendation_engine
This is base-line approach for building job recommendation engine
https://github.com/jalajthanaki/basic_job_recommendation_engine
basics job-recommendation
Last synced: about 1 year ago
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This is base-line approach for building job recommendation engine
- Host: GitHub
- URL: https://github.com/jalajthanaki/basic_job_recommendation_engine
- Owner: jalajthanaki
- Created: 2018-04-09T08:55:43.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2018-04-11T06:11:32.000Z (about 8 years ago)
- Last Synced: 2025-03-23T18:54:20.995Z (over 1 year ago)
- Topics: basics, job-recommendation
- Language: Python
- Size: 4.08 MB
- Stars: 13
- Watchers: 2
- Forks: 8
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Job Recommendation System base line approach
This is simple job recommendation system. A base line approach.
## Dependencies
* math
* dill
* pickel
* scikit-learn
* pdfminer
* urllib2
* requests
* re
* os
* sys
## Installation
```
* math: By default installed
* dill: $ sudo pip install dill
* pickle: $ sudo pip install pickle
* scikit-learn: $ sudo pip install sklearn
* pdfminer: $ sudo pip install pdfminer
* urllib2: By default installed for python 2.7 for python 3 use this: import urllib.request as urllib2
* requests: $ sudo pip install requests
* re: By default installed
* os: By default installed
* sys: By default installed
```
## Usage
* I have already generated pixel file for dataset.
* In order to run the scrip and generate the training score you need to run the script `tfidf.py`
* `indeed_scrap.py` scrap the data and `pdf_parse.py` used to parse the pdf files.
## credit
Credits for this code go to [xyaoinum](https://github.com/xyaoinum). I've merely created a wrapper to get people started.