semantic-search-cwicr
Semantic Search in DDC CWICR Database
Business Case
Problem Statement
Construction cost estimation requires finding relevant work items from large databases. Traditional keyword search fails when:
- Users describe work in natural language
- Terminology varies across regions and languages
- Similar work items have different naming conventions
Solution
DDC CWICR database provides pre-computed embeddings (OpenAI text-embedding-3-large, 3072 dimensions) enabling semantic similarity search across 55,719 work items in 9 languages.
Business Value
- 90% faster work item lookup compared to manual search
- Multi-language support: Arabic, Chinese, German, English, Spanish, French, Hindi, Portuguese, Russian
- Higher accuracy by finding semantically similar items, not just keyword matches
Technical Implementation
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