Don't Forget This: Augmenting Results with Event-Aware Search

Events like Valentine's Day and Christmas can influence user intent when interacting with search engines. For example, a user searching for gift around Valentine's Day is likely to be looking for Valentine's-themed options, whereas the same query close to Christmas would more likely suggest an interest in Holiday-themed gifts. These shifts in user intent, driven by temporal factors, are often implicit but important to determine the relevance of search results. In this demo, we explore how incorporating temporal awareness can enhance search relevance in an e-commerce setting. We constructed a database of 2K events and, using historical purchase data, developed a temporal model that estimates each event's importance on a specific date. The most relevant events on the date the query was issued are then used to enrich search results with event-specific items. Our demo illustrates how this approach enables a search system to better adapt to temporal nuances, ultimately delivering more contextually relevant products.

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Publication Details

Published
2025-02-26
DOI
https://doi.org/10.1145/3701551.3704119
Primary Topic
Advanced Database Systems and Queries
Type
article
Field-Weighted Citation Impact
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article

Don't Forget This: Augmenting Results with Event-Aware Search

Austin R. Ward, Omar Alonso, Hugo Sousa
Advanced Database Systems and Queries
article

Don't Forget This: Augmenting Results with Event-Aware Search

Austin R. Ward, Omar Alonso, Hugo Sousa
article en

Abstract

Events like Valentine's Day and Christmas can influence user intent when interacting with search engines. For example, a user searching for gift around Valentine's Day is likely to be looking for Valentine's-themed options, whereas the same query close to Christmas would more likely suggest an interest in Holiday-themed gifts. These shifts in user intent, driven by temporal factors, are often implicit but important to determine the relevance of search results. In this demo, we explore how incorporating temporal awareness can enhance search relevance in an e-commerce setting. We constructed a database of 2K events and, using historical purchase data, developed a temporal model that estimates each event's importance on a specific date. The most relevant events on the date the query was issued are then used to enrich search results with event-specific items. Our demo illustrates how this approach enables a search system to better adapt to temporal nuances, ultimately delivering more contextually relevant products.

Amazon (United States) (US), Universidade do Porto (PT), INESC TEC (PT)
Openalex Percentile: Top 97%
Advanced Database Systems and Queries
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