Graph Analysis and Community Detection Enhancement

2 min read

Graph Analysis and Community Detection Enhancement

  • Day: 2025-09-12
  • Time: 12:00 to 15:40
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Graph Analysis, Community Detection, Python Scripting, Data Processing, Knowledge Base

Description

Session Goal

The session aimed to enhance graph analysis techniques and community detection strategies through detailed metric evaluation and Python scripting.

Key Activities

  • Conducted a detailed analysis of graph structures, focusing on metrics like quantiles, support, lift, and nPMI to inform community detection thresholds.
  • Developed Python scripts for processing CSV files, creating tag-pair views, and generating edge-related outputs with quantile-based thresholds.
  • Explored the geography of knowledge through metrics analysis and provided recommendations for knowledge base optimization.
  • Implemented refined data processing techniques, including anti-tautology guards and tag normalization, to improve data processing workflows.
  • Addressed import and keyword argument errors in Python scripts, enhancing the functionality of the kb_eda package.
  • Evaluated and improved community alignment and edge scoring methods, providing actionable refinements.

Achievements

  • Established parameter tiers for filtering edges in graph analysis.
  • Successfully created various tag-pair subsets and enhanced data processing scripts.
  • Improved the organization and navigation of the knowledge base through metric analysis.
  • Resolved technical issues in Python scripts, leading to more robust data processing capabilities.

Pending Tasks

  • Further alignment of tag vocabularies to prevent mismatches in community mapping.
  • Continued development of CLI tools for chapter generation and community mapping.
  • Ongoing refinement of data processing scripts to enhance community detection accuracy.

Evidence

  • source_file=2025-09-12.sessions.jsonl, line_number=2, event_count=0, session_id=c6ccc01072e4728da43e24a7311b07585ddb6bb5ea9ed8f96a6b67da548be294
  • event_ids: []

Graph View

Backlinks