Created
December 18, 2023 21:45
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Reciprocal Rank Fusion implementation
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| from collections import defaultdict | |
| def reciprocal_rank_fusion(*list_of_list_ranks_system, K=60): | |
| """ | |
| Fuse rank from multiple IR systems using Reciprocal Rank Fusion. | |
| Args: | |
| * list_of_list_ranks_system: Ranked results from different IR system. | |
| K (int): A constant used in the RRF formula (default is 60). | |
| Returns: | |
| Tuple of list of sorted documents by score and sorted documents | |
| """ | |
| # Dictionary to store RRF mapping | |
| rrf_map = defaultdict(float) | |
| # Calculate RRF score for each result in each list | |
| for rank_list in list_of_list_ranks_system: | |
| for rank, item in enumerate(rank_list, 1): | |
| rrf_map[item] += 1 / (rank + K) | |
| # Sort items based on their RRF scores in descending order | |
| sorted_items = sorted(rrf_map.items(), key=lambda x: x[1], reverse=True) | |
| # Return tuple of list of sorted documents by score and sorted documents | |
| return sorted_items, [item for item, score in sorted_items] | |
| # Example ranked lists from different sources | |
| ir_system_a = ['Document1', 'Document3', 'Document5', 'Document7'] | |
| ir_system_b = ['Document2', 'Document1', 'Document4'] | |
| ir_system_c = ['Document5', 'Document3', 'Document2'] | |
| # Combine the lists using RRF | |
| combined_list = reciprocal_rank_fusion(ir_system_a, ir_system_b, ir_system_c) | |
| print(combined_list) |
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