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2019 IEEE International Congress on Big Data (BigDataCongress)最新文献

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IEEE BigData Congress 2019 Reviewers IEEE大数据大会2019审稿人
Pub Date : 2018-07-01 DOI: 10.1109/bigdatacongress.2018.00007
Karl, Alvares De Oliveira, Frederico, Amini Salehi, Mohsen, Awad, Ahamed, Bacardit, Jaume, Barnaghi, Payam, Barros, Rodrigo Balaji, Buduru, Arun, Calheiros, N. Rodrigo, Cano, Alberto, Cao, Xin, Cárdenas Montes, Miguel, Cautis, Bogdan, Cesario, Eugenio, Chatterjee, Matthew, Fumarola, Antonio, Granado-Criado, M. José, Gruenwald, Jonathan, Masoumzadeh, Mutharaju, Raghava, Navarro, A. Cristóbal, Netto, Yusuke, Özcan, Ender, Parkes, J. Andrew, Peralta
Aberer, Karl Alvares De Oliveira, Frederico Amini Salehi, Mohsen Awad, Ahamed Bacardit, Jaume Barnaghi, Payam Barros, Rodrigo Balaji Buduru, Arun Calheiros, Rodrigo N. Cano, Alberto Cao, Xin Cárdenas Montes, Miguel Cautis, Bogdan Cesario, Eugenio Chatterjee, Subarna Chen, Lisi Chen, Peng Choi, Byron Cuadrado, Félix Curry, Edward Da Silva, Dilma Dai, Dong Dai, Hong-Ning Dazzi, Patrizio Di, Sheng Diván, Mario José Djenouri, Youcef Dorier, Matthieu Dridi, Amna Dustdar, Schahram Fabiana, Pasqua Fan, Liyue Fletcher, George H.L. Forshaw, Matthew Fumarola, Fabio G.R., Gangadharan Gaber, Mohamed Galar, Mikel Gómez-Iglesias, Antonio Granado-Criado, Jose M. Gruenwald, Le Gryz, Jarek Guo, Yanfei Hamlich, Mohamed Hao, Jin-Kao Hara, Takahiro He, Jiong He, Qiang Herrera, Francisco Hidders, Jan Hu, Liting Huang, Xin Ishikawa, Yoshiharu Javadi, Bahman Karatza, Helen Kechadi, Tahar Khalifa, Shadi Khayyat, Zuhair Kheiri, Ahmed Koch, Fernando Koldehofe, Boris Kuhn, Michael Lee, Young Choon Li, Yusen Li, Zengxiang Liao, Hao Limet, Sébastien Liu, Haikun Lodi, Andrea Lu, Hua Lu, Xiaoyi Lughofer, Edwing Magdy, Amr Malerba, Donato Malik, Tanu Malin, Brad Marcelloni, Francesco Marozzo, Fabrizio Martí, Jonathan Masoumzadeh, Amirreza Molina-Solana, Miguel Mutharaju, Raghava Navarro, Cristobal A. Netto, Marco Nojima, Yusuke Özcan, Ender Parkes, Andrew J. Peralta, Daniel Provetti, Alessandro Qi, Lianyong Qin, Yongrui Queralt, Anna Renso, Chiara Rodero, Ivan Romero, Oscar Ropars, Thomas Rubio-Largo, Alvaro Sakr, Sherif Samanthula, Bharath Kumar Samarati, Pierangela Santander-Jiménez, Sergio Sanz Delgado, José Antonio Schunter, Matthias Shi, Weidong Simonet, Anthony Singh, Neeraj Singhal, Rekah Strohbach, Martin Taheri, Javid Talia, Domenico Tang, Shanjiang Tao, Dingwen Torres Torres, Mercedes Vega-Rodríguez, Miguel A. Ventura, Sebastián Vernier, Matthieu Villar, José Ramón Wang, Cheng Wang, Hao
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引用次数: 0
BiDaML: A Suite of Visual Languages for Supporting End-User Data Analytics BiDaML:一套支持最终用户数据分析的可视化语言
Pub Date : 1900-01-01 DOI: 10.1109/BigDataCongress.2019.00025
Hourieh Khalajzadeh, Mohamed Abdelrazek, J. Grundy, J. Hosking, Qiang He
We introduce Big Data Analytics Modeling Languages (BiDaML), a novel integrated suite of visual languages aimed at supporting end users during the process of designing big data analytics solutions. BiDaML comprises five diagrammatic notations: a data analytics brainstorming diagram; a process diagram; technique diagrams; data diagrams; and output diagrams. Tool support in the form of an integrated design environment for creating BiDaML diagrams has also been developed. To demonstrate the utility of BiDaML, we illustrate our approach with a real-world example of property price prediction and evaluate BiDaML using the physics of notations and cognitive walkthroughs with target end users - data scientists and software engineers.
我们介绍了大数据分析建模语言(BiDaML),这是一套新颖的可视化语言,旨在为最终用户在设计大数据分析解决方案的过程中提供支持。BiDaML包括五个图表符号:数据分析头脑风暴图;工艺流程图;技术图表;数据图;输出图。还开发了用于创建BiDaML图的集成设计环境形式的工具支持。为了演示BiDaML的实用性,我们用一个真实世界的房地产价格预测示例来说明我们的方法,并使用物理符号和与目标最终用户(数据科学家和软件工程师)的认知预演来评估BiDaML。
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引用次数: 14
期刊
2019 IEEE International Congress on Big Data (BigDataCongress)
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