Using Text-Based Web Image Search Results Clustering to Minimize Mobile Devices Wasted Space-Interface

Gaël Dias (1)

1 Equipe Hultech - Laboratoire GREYC - UMR6072

The recent shift in human-computer interaction from desk-top to mobile computing fosters the needs of new interfaces for web image search results exploration. In order to leverage users' efforts, we present a set of state-of-the-art ephemeral clustering algorithms, which allow to summarize web image search results into meaningful clusters. This way of presenting visual information on mobile devices is exhaustively eval-uated based on two main criteria: clustering accuracy, which must be maximized, and wasted space-interface, which must be minimized. For the first case, we use a broad set of metrics to evaluate ephemeral clus-tering over a public golden standard data set of web images. For the second case, we propose a new metric to evaluate the mismatch of the used space-interface between the ground truth and the cluster distribu-tion obtained by ephemeral clustering. The results evidence that there exist high divergences between clustering accuracy and used space maxi-mization. As a consequence, the trade-off of cluster-based exploration of web image search results on mobile devices is difficult to define, although our study evidences some clear positive results.

Domaines: Traitement du texte et du document

Gaël Dias. Using Text-Based Web Image Search Results Clustering to Minimize Mobile Devices Wasted Space-Interface. 34th European Conference on Information Retrieval (ECIR 2013), Mar 2013, moscou, Russia. pp.532 - 544, ⟨10.1007/978-3-642-36973-5_45⟩. ⟨hal-01074557⟩