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231225s2021 xx |||||o 00| ||eng c |
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|a 10.1109/MCG.2020.2973939
|2 doi
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|a pubmed25n1022.xml
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|a eng
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| 100 |
1 |
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|a Ma, Chao
|e verfasserin
|4 aut
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| 245 |
1 |
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|a CLEVis
|b A Semantic Driven Visual Analytics System for Community Level Events
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|c 2021
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|a Text
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|a Date Completed 27.09.2021
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|a Date Revised 27.09.2021
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a 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
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|a Journal Article
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|a Research Support, U.S. Gov't, Non-P.H.S.
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1 |
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|a Zhao, Ye
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Curtis, Andrew
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Kamw, Farah
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Al-Dohuki, Shamal
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Yang, Jing
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Jamonnak, Suphanut
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Ali, Ismael
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE computer graphics and applications
|d 1991
|g 41(2021), 2 vom: 14. März, Seite 49-62
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|x 1558-1756
|7 nnas
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|g volume:41
|g year:2021
|g number:2
|g day:14
|g month:03
|g pages:49-62
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|u http://dx.doi.org/10.1109/MCG.2020.2973939
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