Ahsan Morshed, Pei-wei Tsai, P. Jayaraman, T. Sellis, Dimitrios Georgakopoulos, Samuel V. S. Burke, Shane Joachim, Ming-Sheng Quah, Stefan Tsvetkov, Jason Liew, C. Jenkins
{"title":"VisCrime: A Crime Visualisation System for Crime Trajectory from Multi-Dimensional Sources","authors":"Ahsan Morshed, Pei-wei Tsai, P. Jayaraman, T. Sellis, Dimitrios Georgakopoulos, Samuel V. S. Burke, Shane Joachim, Ming-Sheng Quah, Stefan Tsvetkov, Jason Liew, C. Jenkins","doi":"10.1145/3289600.3290617","DOIUrl":null,"url":null,"abstract":"Open multidimensional data from existing sources and social media often carries insightful information on social issues. With the increase of high volume data and the proliferation of visual analytics platforms, users can more easily interact with and pick out meaningful information from a large dataset. In this paper, we present VisCrime, a system that uses visual analytics to maps out crimes that have occurred in a region/neighbourhood. VisCrime is underpinned by a novel trajectory algorithm that is used to create trajectories from open data sources that reports incidents of crime and data gathered from social media. Our system can be accessed at http://viscrime.ml/deckmap","PeriodicalId":143253,"journal":{"name":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","volume":"166 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3289600.3290617","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Open multidimensional data from existing sources and social media often carries insightful information on social issues. With the increase of high volume data and the proliferation of visual analytics platforms, users can more easily interact with and pick out meaningful information from a large dataset. In this paper, we present VisCrime, a system that uses visual analytics to maps out crimes that have occurred in a region/neighbourhood. VisCrime is underpinned by a novel trajectory algorithm that is used to create trajectories from open data sources that reports incidents of crime and data gathered from social media. Our system can be accessed at http://viscrime.ml/deckmap