📅 2024-07-12 — Session: Implemented Fuzzy Matching and Many-to-Many Search
🕒 03:05–03:55
🏷️ Labels: Fuzzy Matching, Elasticsearch, Python, Data Processing, Entity Recognition
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to implement a many-to-many search mechanism linking individuals to pages and to develop a fuzzy matching system for entity recognition in data frames.
Key Activities
- Developed a structured approach for many-to-many search using Elasticsearch for indexing and querying relevant pages.
- Implemented fuzzy matching techniques using Python’s pandas and fuzzywuzzy libraries to match entities between data frames.
- Created Python code snippets to handle lists of tuples in data frames and perform fuzzy matching.
Achievements
- Successfully implemented a many-to-many search mechanism using Elasticsearch.
- Developed a robust fuzzy matching system for entity recognition between data frames.
- Created reusable Python code for fuzzy matching and data processing tasks.
Pending Tasks
- Further optimization of the fuzzy matching algorithm for larger datasets.
- Integration of the current implementation into a larger data processing pipeline.