Abstract
We have developed a browser suitable for finding events from timelines, in particular from life logs and other timelines containing a familiar narrative. The system infers the relevance of events based on the user’s browsing behavior and increases the visual saliency of relevant items along the timeline. As recognized images are strong memory cues, the user can quickly determine if the salient images are relevant and, if they are, it is quick and easy to select them by clicking since they are salient. Even if the inferred relevance was not correct, the timeline will help: The user may remember if the sought event was before or after a saliently shown event which limits the search space. A user study shows that the browser helps in locating relevant images quicker, and augmenting explicit click feedback with implicit mouse movement patterns further improves the performance.
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Ajanki, A., Kaski, S. (2011). Probabilistic Proactive Timeline Browser. In: Honkela, T., Duch, W., Girolami, M., Kaski, S. (eds) Artificial Neural Networks and Machine Learning – ICANN 2011. ICANN 2011. Lecture Notes in Computer Science, vol 6792. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21738-8_46
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DOI: https://doi.org/10.1007/978-3-642-21738-8_46
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