Image Results Exploration using Ephemeral Clustering
Résumé
The recent shift in human-computer interaction from desktop to mobile computing fosters the needs of new interfaces for web image search results exploration. We present two different strategies to cluster results gathered from a text- based image search engine and propose an adapted interface for handled devices. For that purpose, we suggest to expand the original text query based on labels of ephemeral text clusters and compare it to a query log-based approach. In particular, we present a new ephemeral clustering algorithm, the HISGK-means, which proposes a more compact representation of web search results compared to the commonly used STC algorithm and best fits to the mobile devices constraints by limiting browsing and zooming.
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