BM25
Core algorithm components:
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Term frequency weighting
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Document length normalization
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Inverse document frequency
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Parameter optimization
Neural Ranking
Deep learning approaches:
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Transformer architectures
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Cross-attention mechanisms
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Contextual embeddings
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Fine-tuning strategies
Hybrid Scoring
Combined methods:
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BM25 and neural fusion
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Weighted ensemble scoring
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Feature combination strategies
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Performance optimization
Re-ranking
Refinement process:
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Initial candidate selection
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Deep semantic scoring
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Context-aware filtering
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Result reordering