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首页> 外文期刊>IEEE Computer Graphics and Applications >CLEVis: A Semantic Driven Visual Analytics System for Community Level Events
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CLEVis: A Semantic Driven Visual Analytics System for Community Level Events

机译:CLEVIS:社区级事件的语义驱动视觉分析系统

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摘要

Community-level event (CLE) datasets, such as police reports of crime events, contain abundant semantic information of event situations, and descriptions in a geospatial-temporal context. They are critical for frontline users, such as police officers and social workers, to discover and examine insights about community neighborhoods. We propose CLEVis, a neighborhood visual analytics system for CLE datasets, to help frontline users explore events for insights at community regions of interest, namely fine-grained geographical resolutions, such as small neighborhoods around local restaurants, churches, and schools. CLEVis fully utilizes semantic information by integrating automatic algorithms and interactive visualizations. The design and development of CLEVis are conducted with solid collaborations with real-world community workers and social scientists. Case studies and user feedback are presented with real-world datasets and applications.
机译:社区级事件(CLE)数据集如警察犯罪事件的报告,包含了富有的事件情况的语义信息,以及地理空间上下文中的描述。它们对于前线用户(例如警察和社会工作者)至关重要,以发现和审视社区社区的见解。我们提出了CLEVIS的CLEVIS,用于CLE数据集,帮助前线用户探索社区兴趣区域的见解,即细粒度的地理决议,如当地餐馆,教堂和学校周围的小社区。 CLEVIS通过集成自动算法和交互式可视化来充分利用语义信息。 CLEVIS的设计和开发与实际合作与现实世界的社区工作者和社会科学家进行。案例研究和用户反馈显示了现实世界数据集和应用程序。

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