Scalable Image-based Search-and-Discovery.
CHI Extended Abstracts(2017)
摘要
People use online search-and-discovery services, such as Yelp, by first finding a specific item with keywords and then examining the images linked to the item. Images could constitute an important part of users' decision-making process but users reach them indirectly. Although recently researchers proposed several image-based search interfaces, how they can effectively arrange huge number of images in a scalable manner is still not clear. To address this, we introduce PicNav, an image-driven navigation system that automatically arranges photos according to their semantic similarity. PicNav is built on deep neural networks learned from the Yelp food dataset and enables effective zoom-in/out features. We conducted interviews with ten users to qualitatively assess the system's usability. The users identified a number of advantages of PicNav, providing insights into the general use of imagery in search-and-discovery services.
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关键词
image-based,search-and-discovery
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