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Among the different personality traits that guide our behaviour, curiosity is particularly interesting for context-aware assistive systems as it is closely linked to our well-being and the way we learn. This work proposes eye movement analysis for automatic recognition of different levels of curiosity. We present a 26-participant gaze dataset recorded during a real-world shopping task with empirically validated curiosity questionnaires as ground truth. Using a support vector machine classifierdoi:10.1145/2800835.2800910 dblp:conf/huc/HoppeLMB15 fatcat:ov6kvg5rnfhgveszzsow7iuf4q