Abstract
Visual search has become popular in recent years, allowing users to search by an image they are taking using their mobile device or uploading from their photo library. One domain in which visual search is especially valuable is electronic commerce, where users seek for items to purchase. In this work, we present an in-depth comprehensive study of visual e-commerce search. We perform query log analysis of one of the largest e-commerce platforms' mobile search application. We compare visual and textual search by a variety of characteristics, with special focus on the retrieved results and user interaction with them. We also examine image query characteristics, refinement by attributes, and performance prediction for visual search queries. Our analysis points out a variety of differences between visual and textual e-commerce search. We discuss the implications of these differences for the design of future e-commerce search systems.
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CITATION STYLE
Dagan, A., Guy, I., & Novgorodov, S. (2021). An Image is Worth a Thousand Terms Analysis of Visual E-Commerce Search. In SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 102–112). Association for Computing Machinery, Inc. https://doi.org/10.1145/3404835.3462950
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