📅 2025-03-04 — Session: Implemented Entity Resolution with Dedupe.io in Jupyter

🕒 22:05–22:40
🏷️ Labels: Entity Resolution, Dedupe, Python, Jupyter, Data Cleaning
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The goal of this session was to implement a robust entity resolution process using the Dedupe.io library within Jupyter Notebooks, addressing common issues and optimizing the deduplication workflow.

Key Activities

  • Reviewed robust entity resolution techniques focusing on clustering records using probabilistic and deterministic matching.
  • Implemented Dedupe.io for probabilistic entity resolution in Python, utilizing active learning and fuzzy matching.
  • Resolved command-line argument conflicts in Jupyter Notebooks related to the optparse library.
  • Adapted a Python script for deduplication using Dedupe in Jupyter, covering data loading to output saving.
  • Corrected syntax for variable definitions in Dedupe 3.0, transitioning from dictionary to direct variable objects.
  • Fixed a ZeroDivisionError in Dedupe by converting empty strings to None.

Achievements

  • Successfully implemented a complete deduplication workflow in Jupyter using Dedupe.io.
  • Resolved technical issues related to command-line arguments and variable definitions.
  • Improved data cleaning processes by addressing common errors and optimizing the deduplication script.

Pending Tasks

  • Further testing of the deduplication script on larger datasets to ensure scalability and efficiency.