Adaptive Chunking—Dynamic Sizes Based on Content Characteristics

I will build an adaptive chunking system — analysing each document's content characteristics (density, structure, technical content, and narrative style) and applying different chunking strategies to different document types and sections within documents, rather than applying a single strategy uniformly across all content. Adaptive chunking is most valuable in corpora with heterogeneous content — a corpus mixing technical documentation (which benefits from structure-aware splitting), narrative text (which benefits from semantic splitting), and tabular data (which benefits from table-preserving splitting) consistently outperforms any single strategy applied uniformly across all content types.

The system covers content classifier for document type and section type detection, strategy assignment per content type, strategy-specific chunking implementation for each content type, unified chunk output with content-type metadata, and quality evaluation comparing adaptive against single-strategy approaches.