Developed Keyword Extraction Class for Data Ingestion

• Day: 2024-10-02
• Time: 03:10 to 03:20
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Keyword Extraction, Data Processing, Automation, NLP, Python

Description

Session Goal

The session aimed to develop a keyword extraction class to process various data sources, facilitating initial classification before further handling by AI agents or storage in specialized databases.

Key Activities

• Planned the creation of a keyword extraction class for processing data from sources like RSS feeds, emails, and news articles.
• Outlined the steps for implementing a flexible keyword extraction and classification system using Python, focusing on techniques like TF-IDF and Named Entity Recognition (NER).
• Confirmed readiness to integrate the keyword extraction class into a data ingestion pipeline.

Achievements

• Successfully outlined the architecture for a flexible data ingestion and processing system.
• Established a clear plan for implementing keyword extraction and classification, setting the stage for further development.

Pending Tasks

• Begin the actual coding and integration of the keyword extraction class into the data ingestion pipeline.
• Test the system with real data sources to ensure functionality and performance.

Evidence

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• event_ids: []