⚡ Bolt: [O(1) Memory Jaccard Similarity]

[garridolecca]

• 💡 What: Replaced O(N) memory allocations (creating new Sets) in jaccardSimilarity with an O(1) loop-based approach. We now iterate the smaller set and check containment in the larger one, and calculate the union mathematically.
• 🎯 Why: jaccardSimilarity is called inside the clusterNewsCore inner loop, which is an O(N^2) operation. Creating two new Sets for every single similarity comparison generates significant garbage collection overhead, dragging down clustering performance as the dataset grows.
• 📊 Impact: O(1) memory footprint per similarity comparison. Reduces massive garbage collection spikes during the news clustering loop.
• 🔬 Measurement: Observe memory profiling during news processing/clustering. You should see a marked drop in minor GC sweeps since intermediate arrays and sets are no longer allocated in bulk.

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PR created automatically by Jules for task 17498396113758693928 started by @garridolecca

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