Hybrid Embedding and BM25 Semantic Matching Pipeline
I executed semantic text matching using embeddings and scoring to surface distinctive passages.
- Machine Learning
- Natural Language Processing
- Latent Semantic Analysis
- Python
- Word Embedding
5 projects.
Other categories
I executed semantic text matching using embeddings and scoring to surface distinctive passages.
I built a semantic ranking system using ML with configurable similarity, scoring, and exclusion models.
I extracted 4,000 records from old PDF book scans with uneven OCR'd text in a 3-phase process, then delivered them with a CLI lookup tool.
I mined data for ~4,000 entities in two game systems to create a model based on percentile mapping that converts entities from the old system to the new one.
I built an OCR tool that automatically tunes parameters using grid search to maximize accuracy for each document set.
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