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A Visual Interface for Multivariate Temporal Data: Finding Patterns of Events across Multiple Histories

机译:用于多变量时间数据的可视界面:在多个历史上查找事件模式

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Finding patterns of events over time is important in searching patient histories, web logs, news stories, and criminal activities. This paper presents Pattern Finder, an integrated interface for query and result-set visualization for search and discovery of temporal patterns within multivariate and categorical data sets. We define temporal patterns as sequences of events with inter-event time spans. Pattern Finder allows users to specify the attributes of events and time spans to produce powerful pattern queries that are difficult to express with other formalisms. We characterize the range of queries Pattern Finder supports as users vary the specificity at which events and time spans are defined. Pattern Finder's query capabilities together with coupled ball-and-chain and tabular visualizations enable users to effectively query, explore and analyze event patterns both within and across data entities (e.g. patient histories, terrorist groups, web logs, etc.).
机译:在搜索患者历史,网络日志,新闻报道和犯罪活动中,查找随着时间的推移模式是重要的。本文呈现了模式查找器,一个用于查询的集成接口,用于搜索多变量和分类数据集中的时间模式的搜索和发现。我们将时间模式定义为具有帧间活动时间跨度的事件序列。模式查找器允许用户指定事件和时间跨度的属性,以产生难以与其他形式主义表达的强大模式查询。当用户改变定义事件和时间跨度的特异性时,我们表征了查询模式查询范围支持的范围。模式搜索器的查询功能与耦合的球链和表格可视化一起使用户能够有效地查询,探索和分析数据实体内和跨数据实体的事件模式(例如患者历史,恐怖主义组,Web日志等)。

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