TY - GEN
T1 - An Image is Worth a Thousand Terms Analysis of Visual E-Commerce Search
AU - Dagan, Arnon
AU - Guy, Ido
AU - Novgorodov, Slava
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/7/11
Y1 - 2021/7/11
N2 - 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.
AB - 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.
KW - e-commerce search
KW - product search
KW - query log analysis
KW - query performance prediction
KW - search by image
KW - visual search
UR - https://www.scopus.com/pages/publications/85111648037
U2 - 10.1145/3404835.3462950
DO - 10.1145/3404835.3462950
M3 - Conference contribution
AN - SCOPUS:85111648037
T3 - SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 102
EP - 112
BT - SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
PB - Association for Computing Machinery, Inc
T2 - 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2021
Y2 - 11 July 2021 through 15 July 2021
ER -