Resolved

Tech term extraction relies on hardcoded lists instead of automatic discovery

NLP
Documentation
Automation
Python
Semantic Analysis
Regex
Data Processing
Frontend

Documentation system used static COMMON_TECH_TERMS array preventing true automatic technology term extraction | Solution implements regex-based discovery with semantic classification

A Python-based natural language processing system for documentation relied on manually curated lists of technology terms, limiting its ability to automatically discover new technologies mentioned in documentation.

Issue

The documentation pipeline used a hardcoded list of ~60 technology terms, requiring manual updates whenever new technologies were introduced. This static approach prevented the system from automatically detecting emerging terms and failed to scale with the growing documentation corpus (1993 files with 957 unique technologies).

Culprit

The original design depended on a predefined list of technology terms, which could not identify new or evolving technologies. This required manual intervention for updates and did not leverage the full potential of automated discovery.

Solution

Automatic Term Extraction

A regex-based system was implemented to automatically identify technology terms from documentation text. The system detects terms using patterns for:

  • Capitalized words (e.g., Docker)
  • All-caps terms (e.g., AWS)
  • CamelCase and hyphenated formats (e.g., useState, scikit-learn)
  • Dotted formats (e.g., D3.js)

Frequency-Based Filtering

Extracted terms must meet thresholds such as:

  • Appearing in at least 5 documents.
  • Occurring at least 10 times in total.
  • Having a length between 2 and 30 characters.

Semantic Classification

Instead of relying on hardcoded categories, the system uses semantic similarity to classify terms as frameworks, libraries, or other categories. This approach dynamically adapts to new technologies without requiring predefined lists.

Dynamic Frontend Integration

The top technology terms are automatically integrated into the frontend, allowing users to browse the most relevant and frequently mentioned technologies. This eliminates manual updates and ensures the documentation system remains current with the latest technologies.

Performance and Maintenance

While processing time increased due to the expanded scope, the system now automatically discovers new technologies whenever they meet the defined criteria. This reduces maintenance overhead and improves the accuracy of technology term extraction.