User-specific behavioral signals, especially prior search queries, outperform population-level demand patterns and static profiles for inferring gender, age, category, and size from underspecified e-commerce queries.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '23), July 23--27, 2023, Taipei, Taiwan , series =
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IntentTune: Using user demand and personalization to resolve "unknown" query intents for e-commerce search
User-specific behavioral signals, especially prior search queries, outperform population-level demand patterns and static profiles for inferring gender, age, category, and size from underspecified e-commerce queries.