TY - CONF TI - Faceted Metadata for Image Search and Browsing AU - Yee, Ka-Ping AU - Swearingen, Kirsten AU - Li, Kevin AU - Hearst, Marti T3 - CHI '03 AB - There are currently two dominant interface types for searching and browsing large image collections: keyword-based search, and searching by overall similarity to sample images. We present an alternative based on enabling users to navigate along conceptual dimensions that describe the images. The interface makes use of hierarchical faceted metadata and dynamically generated query previews. A usability study, in which 32 art history students explored a collection of 35,000 fine arts images, compares this approach to a standard image search interface. Despite the unfamiliarity and power of the interface (attributes that often lead to rejection of new search interfaces), the study results show that 90% of the participants preferred the metadata approach overall, 97% said that it helped them learn more about the collection, 75% found it more flexible, and 72% found it easier to use than a standard baseline system. These results indicate that a category-based approach is a successful way to provide access to image collections. C1 - New York, NY, USA C3 - Proceedings of the SIGCHI Conference on Human Factors in Computing Systems DA - 2003/// PY - 2003 DO - 10.1145/642611.642681 DP - ACM Digital Library SP - 401 EP - 408 LA - en PB - ACM SN - 978-1-58113-630-2 UR - http://doi.acm.org/10.1145/642611.642681 Y2 - 2018/08/09/19:17:02 ER -