/Career_Platform_with_Demo

Source Code and Demo for paper CareerMiner: Automatic Extraction of Professional Network from Large Chinese Resume Data

Primary LanguagePythonMIT LicenseMIT

Career Platform with Demo

Welcome to the Career Platform! This project is designed to analyze Chinese resumes and extract important career relationships about the working experiences of each person, providing you with segmentation results and a career social network visualization. You can also try our demo on http://8.129.175.102/CareerMiner/

Parts of Code

The system consists of several main components, including:

  • app: This is the Vue application that serves as demo of the system. It handles the user input, sends it to the appropriate modules for processing and presents the results in a clear and concise manner.
  • Career_API: This module handles interface between demo and backend algorithms.
  • Career_Platform: Main part of the system. This module processes the text data, builds OCTree and extracts Career Social Network based on Neo4j.
  • runApp.py: A simple script which helps turn on Career_API.
  • sample_resumes.txt: Some sample data, the format needed for the demo's input.

Installation and Running Steps

To run the Career Platform Demo, follow these steps:

  1. Clone the repository to your local machine using git clone https://github.com/kundtx/Career_Platform_with_Demo.git.
  2. Install the required libraries using pip install -r requirements.txt. A python environment with version 3.8.x is recommended.
  3. Install and run the Neo4j database. Version 3.5.x is recommended.
  4. Prepare Career_Platform by following these steps:
    1. Download the chinese_L-12_H-768_A-12, convert tf checkpoints to pytorch, and put the folder in Career_Platform\career_platform\algorithm\exp_parser\segment\ner\ckpts\
    2. execute python career_platform\algorithm\exp_parser\segment\ner\bert.py at the command line
    3. execute python career_platform\algorithm\exp_parser\segment\ner\parser.py at the command line
  5. Run the Career_API using python runApp.py.
  6. Run the app using npm run dev under its folder.
  7. Enjoy the demo:
    1. Open your web browser and navigate to http://localhost:8080.
    2. Enter a list of Chinese resumes separated by the # symbol, with each working experience listed on a separate line and the working period indicated at the beginning of each line in the format of yyyy.mm-yyyy.mm.
    3. Click the "Start Analysis" button to analyze the resumes and view the results.
    4. Click the "Synchronize Data" buttons under OCTree and CSN parts to view the corresponding visualizations.