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Location Fix Analysis for Enhanced Intent Detection

Testing Results Summary

We conducted tests to evaluate how our system handles location-based queries, particularly focusing on how the location transfer fix would impact search results. Our test query was: "What things i can do at a park in sf".

Current System Behavior

The current system already correctly identifies "San Francisco" in the top-level locations array for this query. This is likely because the query analysis function is already effective at identifying "sf" as a location and properly adding it to the locations array for this particular query pattern.

Current analysis JSON:

{
  "id": null,
  "entities": {
    "feature": ["things to do"],
    "attribute": ["park", "sf"]
  },
  "topics": ["park activities", "San Francisco"],
  "locations": ["San Francisco"],
  "intent": "discovery"
}

Impact of Intent on Boosting Strategy

Our tests revealed that the intent type significantly affects how boosting is applied in the multi-strategy search function:

With "information" intent:

  • 6 basic results
  • 4 location_boosted results
  • 0 context_enhanced results

With "discovery" intent:

  • 5 basic results
  • 0 location_boosted results
  • 5 context_enhanced results

This shows that the multi-strategy search function applies different boosting strategies depending on the intent. For "information" intent, location boosting is prioritized, while for "discovery" intent, context enhancement is prioritized.

The Location Fix

While our location transfer fix doesn't show a significant impact for this specific query (since "San Francisco" is already correctly identified), it would still be valuable for other queries where:

  1. The location is only detected in entities.location
  2. The location is in abbreviated form that isn't automatically expanded

The fix ensures that any location detected in entities.location is:

  1. Normalized (expanding abbreviations like "sf" to "San Francisco")
  2. Transferred to the top-level locations array

Conclusion

  1. The multi-strategy search function applies different boosting strategies based on the intent type
  2. The location transfer fix would be most useful for queries where locations are not already being properly identified and transferred
  3. For our test query, the current system is already effectively identifying "San Francisco" as a location, which explains why we didn't see a dramatic improvement from the fix

Next Steps

  1. Test with additional queries where locations might not be properly identified
  2. Evaluate how the intent recognition affects boosting strategy across different types of queries
  3. Consider whether the boosting strategy difference between intents is intentional and optimal