Stefan Oehmcke

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Diary studies are often applied in HCI research to collect qualitative user impressions. Unfortunately, the period between creation of a diary entry and the later reflection can be too long, which leads to a limited currentness and contextuality. This eventually results in incomplete or misinterpreted data. In this paper we present Storyteller, a mobile(More)
The imputation of partially missing multivariate time series data is critical for its correct analysis. The biggest problems in time series data are consecutively missing values that would result in serious information loss if simply dropped from the dataset. To address this problem, we adapt the k-Nearest Neighbors algorithm in a novel way for multivariate(More)
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