Skip to content

RELEASE_NOTES_v1.0.0.md

Latest commit

 

History

History
151 lines (114 loc) · 4.94 KB

RELEASE_NOTES_v1.0.0.md

File metadata and controls

151 lines (114 loc) · 4.94 KB

IAB Mapper v1.0.0 Release Notes

🎉 Major Release: IAB Mapper v1.0.0

This is the first major release of the IAB Mapper, marking its readiness for production use and contribution to the IAB Tech Lab community.

🚀 What's New

Official IAB Tech Lab Contribution

  • Formal donation to IAB Tech Lab under BSD 2-Clause license
  • RF RAND mode compliance for royalty-free usage
  • Industry-ready for IAB member adoption

Enhanced Sample Datasets

  • Official IAB samples based on Content Taxonomy 2.2
  • 60+ realistic categories including subcategories
  • Vector attributes examples (channel, type, format, language, source, environment)
  • Free-text challenges for semantic matching testing

Improved Documentation

  • Enablement-ready README with 5-minute quickstart
  • Comprehensive CONTRIBUTING.md with development guidelines
  • Enhanced issue templates for better bug reports and feature requests
  • Official samples documentation with usage examples

License Update

  • BSD 2-Clause License (previously MIT) for IAB Tech Lab compatibility
  • Open source compliance with industry standards

🔧 Technical Features

Core Functionality

  • Deterministic matching → fuzzy matching → optional semantic enhancement
  • Local-first processing with no external API dependencies
  • OpenRTB/VAST compatibility with proper IAB 3.0 ID output
  • SCD awareness for sensitive content handling
  • Vector attributes support for orthogonal taxonomy dimensions

Matching Methods

  • RapidFuzz (default) for fast fuzzy string matching
  • BM25 and TF-IDF alternatives for different use cases
  • Sentence-Transformers embeddings for semantic matching
  • Configurable thresholds for precision/recall tuning

Output Formats

  • CSV and JSON export options
  • OpenRTB content.cat format with configurable cattax
  • VAST CONTENTCAT string format
  • Confidence scores and source attribution
  • Audit trails for unmapped items

📊 Performance & Reliability

Tested Scenarios

  • Official IAB categories with high accuracy mapping
  • Free-text labels with semantic matching
  • Large datasets (100+ items) with consistent performance
  • Edge cases and error handling

Quality Assurance

  • Comprehensive test suite with pytest
  • Sample data validation against official taxonomies
  • Cross-platform compatibility (macOS, Linux, Windows)
  • Python 3.9+ support with modern dependencies

🎯 Use Cases

Ad Tech Industry

  • Contextual targeting migration from 2.x to 3.0
  • Brand safety with SCD-aware mapping
  • OpenRTB integration for programmatic advertising
  • CTV and video content classification

Content Platforms

  • Content categorization for recommendation systems
  • Search and discovery with semantic matching
  • Analytics and reporting with standardized taxonomies
  • Multi-format support (text, video, audio, image)

📦 Installation & Usage

Quick Start

# Install from PyPI
pip install iab-mapper

# Basic usage
iab-mapper sample_data.csv -o mapped_output.json

# With embeddings
iab-mapper sample_data.csv -o mapped_output.json --use-embeddings

Python API

from iab_mapper.pipeline import Mapper, MapConfig
import iab_mapper as pkg

cfg = MapConfig(fuzzy_method="bm25", use_embeddings=True)
data_dir = Path(pkg.__file__).parent / "data"
mapper = Mapper(cfg, str(data_dir))

result = mapper.map_record({"label": "Sports highlights"})

🔗 Resources

🤝 Contributing

We welcome contributions from the IAB community! See CONTRIBUTING.md for guidelines.

Development Setup

git clone https://github.com/mixpeek/iab-mapper.git
cd iab-mapper
python -m venv .venv && source .venv/bin/activate
pip install -e ".[emb]" && pip install -r requirements-dev.txt
pytest -q

📞 Support

  • GitHub Issues: For bug reports and feature requests
  • Documentation: Comprehensive guides and examples
  • Community: IAB Tech Lab member discussions
  • Enterprise: Contact Mixpeek for custom integrations

🎯 Future Roadmap

Multimodal Classification

  • Video content analysis and classification
  • Audio/podcast taxonomy mapping
  • Image recognition for visual content
  • Cross-modal content understanding

Industry Integration

  • IAB member enablement sessions
  • Migration tooling for large-scale deployments
  • Performance optimization for enterprise use
  • API integrations with major ad tech platforms

Ready for IAB Tech Lab contribution and industry adoption! 🚀

This release represents a significant milestone in making IAB 3.0 migration accessible to the entire ad tech ecosystem.