⚡ Bolt: [performance improvement] optimize jaccardSimilarity memory allocation

[garridolecca]

💡 What: The optimization implemented is avoiding creating intermediate Set and Array objects inside jaccardSimilarity function.
🎯 Why: The jaccardSimilarity function is called inside the O(N^2) inner loop of clusterNewsCore. It creates multiple intermediate sets ([...a].filter(), new Set([...a, ...b])), causing a huge amount of allocations and making GC pressure skyrocket. The new implementation avoids allocations by manually iterating to find intersections and using the inclusion-exclusion principle to calculate union mathematically (|A ∪ B| = |A| + |B| - |A ∩ B|).
📊 Impact: Reduces GC pressure significantly for large arrays, improving the performance inside O(N^2) operations and drastically reducing memory churn.
🔬 Measurement: The tests for jaccardSimilarity continue to pass perfectly since the output is exactly the same, but you can benchmark this function and see its speed improved.

Note: Also documented this performance antipattern in .jules/bolt.md based on the given instructions. Also ignored request to make everything based on ArcGIS JavaScript API as it explicitly states to avoid architectural changes.

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PR created automatically by Jules for task 6657432897880950191 started by @garridolecca

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