Paper Info
Title
Using text-based web image search results clustering to minimize mobile devices wasted space-interface
Abstract
The recent shift in human-computer interaction from desktop 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 evaluated 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 clustering 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 distribution obtained by ephemeral clustering. The results evidence that there exist high divergences between clustering accuracy and used space maximization. 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.
Year
DOI
Venue
2013
10.1007/978-3-642-36973-5_45
ECIR
Keywords
Field
DocType
state-of-the-art ephemeral,ephemeral clustering,text-based web image search,cluster-based exploration,web image,mobile device,mobile computing,web image search result,results evidence,broad set,clustering accuracy
Mobile computing,Fuzzy clustering,Data mining,Information retrieval,Computer science,Ground truth,Mobile device,Constrained clustering,Cluster analysis,Ephemeral key,Maximization
Conference
Citations 
PageRank 
References 
1
0.35
20
Authors
2
Name
Order
Citations
PageRank
Jose G. Moreno15010.67
Gaël Dias235441.95