Click-Search: Supporting information search with crowd-powered image-to-keyword query formulation. (June 2018)

• Record Type: Journal Article
• Authors: Yang, Ping-Jing; Wang, Hao-Chuan; Liu, Yu-Hsuan
• Is Part Of: Journal of visual languages & computing. Volume 46(2018)
• Page Start: 12
• Page End: 19
• Publication Date: 2018-06
• Subjects: Search user interface -- Query formulation -- Crowd-powered system -- Search through interaction; Visual programming languages (Computer science) -- Periodicals; Visual programming (Computer science) -- Periodicals; Programming languages (Electronic computers) -- Semantics -- Periodicals; Langages de programmation visuelle -- Périodiques; Programmation visuelle -- Périodiques; Langages de programmation -- Sémantique -- Périodiques; Programming languages (Electronic computers) -- Semantics; Visual programming (Computer science); Visual programming languages (Computer science); Periodicals; Electronic journals; 005
• DOI: 10.1016/j.jvlc.2016.09.002
• Languages: English
• ISSNs: 1045-926X

Abstract

Abstract: Information search is a common yet important task in everyday work and life. It remains challenging how to help users search for information or things they don't know how to express with words. Also, even when people know how to express, the cognitive cost required to retrieve the concepts and formulate the queries can be excessive. In this paper, we present Click-Search, a search user interface that allows people to indicate their search intents by merely selecting and cropping segments of pictures. The system automatically converts cropped image segments to keywords based on known semantic labels at the level of image pixels that are generated by crowdsourced image tagging. Through a user study, we showed that Click-Search could support object-finding activities effectively with a satisfactory user experience.