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• W2912259983 abstract "Temporal event sequences are becoming increasingly important in many application domains such as website click streams, user interaction logs, electronic health records and car service records. A real-world dataset with a large number of event sequences of varying lengths is complex and difficult to analyze. To support visual exploration of the data, it is desirable yet challenging to provide a concise and meaningful overview of sequences. In this paper, we focus on the stage, that is, a frequently occurring subsequence in the dataset. We introduce StageMap, a novel visualization technique to summarize event sequence data into a set of stage progression patterns. The resulting overview is more concise compared with event-level summarization and supports level-of-detail exploration. We further present a visual analytics system with four linked views, which are overview, tree view, stage view and sequences view. We also present case studies and discuss advantages and limitations of applying StageMap to real-world scenarios." @default.
• W2912259983 created "2019-02-21" @default.
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• W2912259983 date "2018-12-01" @default.
• W2912259983 modified "2023-10-10" @default.
• W2912259983 title "StageMap: Extracting and Summarizing Progression Stages in Event Sequences" @default.
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• W2912259983 doi "https://doi.org/10.1109/bigdata.2018.8622571" @default.
• W2912259983 hasPublicationYear "2018" @default.
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