Applicant Tracking System (ATS)

This project implements a backend for an Applicant Tracking System, focusing on efficient CV processing and keyword searching using various string matching algorithms.

Features

• CV Text Extraction: Extracts text content from PDF CVs.
• Information Extraction: Uses regular expressions to extract summaries, skills, job history, and education from CV text.
• Advanced Search Algorithms: Implements and utilizes string matching algorithms for efficient keyword searching:
  • Knuth-Morris-Pratt (KMP): An exact string matching algorithm that efficiently finds occurrences of a "pattern" string within a "text" string. It optimizes by avoiding re-matching characters that are already known to match based on prefixes and suffixes of the pattern.
  • Boyer-Moore (BM): An exact string matching algorithm that typically performs fewer comparisons than KMP, especially on longer patterns. It works by comparing the pattern from right to left and uses a "bad character heuristic" to determine how far to shift the pattern when a mismatch occurs.
  • Aho-Corasick: A multi-pattern string matching algorithm that finds all occurrences of a set of patterns within a text. It builds a Trie-like structure with "failure links" and "output functions" to achieve efficient simultaneous searching.
  • Levenshtein Distance: A fuzzy matching algorithm that calculates the minimum number of single-character edits (insertions, deletions, or substitutions) required to change one word into the other. It's used to determine the similarity percentage between two strings.

Requirements and Installation

Prerequisites

• Python 3.13 or higher: Ensure you have Python version 3.13 or a newer version installed on your system.
• MySQL Server: A running MySQL server instance is required. By default, the application attempts to connect using root as the username and an empty password. If your MySQL configuration differs, you will need to modify the BackendManager initialization call by providing the appropriate db_host, db_user, db_password, and db_name parameters.

Installation

1. Clone the repository:

   git clone https://github.com/fathurwithyou/Tubes3_VitaeLangX.git
   cd src

2. Install uv (a fast Python package installer and runner):

   pip install uv

3. Install Python dependencies using uv:

   uv sync

Building and Running the Program

1. Seed the database: This step will connect to your MySQL server, create the necessary database and tables (if they don't exist), and populate the ApplicationDetail table with CV paths from the data directory. It uses a default applicant profile for all entries.

   uv run seed.py

2. Run the main application: This will initialize the backend, load CV data into memory, and demonstrate search functionalities.

   uv run main.py

Contributors

Nama	NIM
Adinda Putri	13523071
Muhammad Fathur Rizky	13523105
Ahmad Wicaksono	13523121