TY - GEN
T1 - Investigating examination behavior of image search users
AU - Xie, Xiaohui
AU - Liu, Yiqun
AU - Wang, Xiaochuan
AU - Wang, Meng
AU - Wu, Zhijing
AU - Wu, Yingying
AU - Zhang, Min
AU - Ma, Shaoping
N1 - Publisher Copyright:
© 2017 Copyright held by the owner/author(s).
PY - 2017/8/7
Y1 - 2017/8/7
N2 - Image search engines show results differently from general Web search engines in three key ways: (1) mostWeb-based image search engines adopt the two-dimensional result placement instead of the linear result list; (2) image searches show snapshots instead of snippets (query-dependent abstracts of landing pages) on search engine result pages (SERPs); and (3) pagination is usually not (explicitly) supported on image search SERPs, and users can view results without having to click on the "next page" bu.on. Compared with the extensive study of user behavior in general Web search scenarios, there exists no thorough investigation how the different interaction mechanism of image search engines affects users' examination behavior. To shed light on this research question, we conducted an eye-Tracking study to investigate users' examination behavior in image searches. We focus on the impacts of factors in examination including position, visual saliency, edge density, the existence of textual information, and human faces in result images. .ree interesting findings indicate users' behavior biases: (1) instead of the traditional "Golden Triangle" phenomena in the user examination patterns of general Web search, we observe a middle-position bias, (2) besides the position factor, the content of image results (e.g., visual saliency) affects examination behavior, and (3) some popular behavior assumptions in general Web search (e.g., examination hypothesis) do not hold in image search scenarios. We predict users' examination behavior with different impact factors. Results show that combining position and visual content features can improve prediction in image searches.
AB - Image search engines show results differently from general Web search engines in three key ways: (1) mostWeb-based image search engines adopt the two-dimensional result placement instead of the linear result list; (2) image searches show snapshots instead of snippets (query-dependent abstracts of landing pages) on search engine result pages (SERPs); and (3) pagination is usually not (explicitly) supported on image search SERPs, and users can view results without having to click on the "next page" bu.on. Compared with the extensive study of user behavior in general Web search scenarios, there exists no thorough investigation how the different interaction mechanism of image search engines affects users' examination behavior. To shed light on this research question, we conducted an eye-Tracking study to investigate users' examination behavior in image searches. We focus on the impacts of factors in examination including position, visual saliency, edge density, the existence of textual information, and human faces in result images. .ree interesting findings indicate users' behavior biases: (1) instead of the traditional "Golden Triangle" phenomena in the user examination patterns of general Web search, we observe a middle-position bias, (2) besides the position factor, the content of image results (e.g., visual saliency) affects examination behavior, and (3) some popular behavior assumptions in general Web search (e.g., examination hypothesis) do not hold in image search scenarios. We predict users' examination behavior with different impact factors. Results show that combining position and visual content features can improve prediction in image searches.
KW - Examination behavior
KW - Eye-Tracking
KW - Image search
UR - http://www.scopus.com/inward/record.url?scp=85029389411&partnerID=8YFLogxK
U2 - 10.1145/3077136.3080799
DO - 10.1145/3077136.3080799
M3 - Conference contribution
AN - SCOPUS:85029389411
T3 - SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 275
EP - 284
BT - SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval
PB - Association for Computing Machinery, Inc
T2 - 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017
Y2 - 7 August 2017 through 11 August 2017
ER -