Volition - a machine learning decision support platform for Innovate UK
Volition - a machine learning decision support platform for Innovate UK
批准号:
971578
负责人:
金额:
$6.3万
依托单位国家:
英国
项目类别:
Small Business Research Initiative
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --
中文摘要
Volition平台是一个安全的基于云的web应用程序,旨在帮助Innovate UK通过机器学习(ML)更好地利用现有的运营数据。它将由ML功能、自然语言处理(NLP)、高级信息检索技术和数据可视化的混合驱动。Synoptica方法的独特之处在于,我们可以从各种结构化和非结构化来源的网络中自动发现和提取额外的数据,并使用它来增强Innovate UK现有数据的ML分析。该平台将使用ML自动:1)使用最先进的ML/NLP分析和关键字提取,为提交的评估人员分配提供“智能”协助。2)自动检测并突出显示重新提交,重复和重新评估的应用程序3)持续扫描网络,寻找表明公司(和/或财团)成功交付提交中描述的项目的能力的证据。4)允许Innovate UK通过提取数据“信号”以及这些信号之间的联系,以易于理解的图形界面呈现,从而充分利用其现有数据。这种方法将揭示见解和潜在的联系,以帮助Innovate UK更好地理解他们自己的数据。
英文摘要
The Volition platform is a secure cloud based web application designed to help Innovate UK make better use of its existing operational data using machine learning (ML). It will be driven by a blend of ML capabilities, natural language processing (NLP), advanced information retrieval techniques and data visualisation. The Synoptica approach is unique in that we automatically find and extract additional data from the web from a variety of structured and unstructured sources and use this to enhance the ML analysis of Innovate UK’s existing data. This platform will use ML to automatically: 1) Provide ‘smart’ assistance with assessor allocation for submissions using state of the art ML/NLP profiling and keyword extraction. 2) Automatically detect and highlight re-submissions, duplicate and reassessed applications 3) Scan the web continuously finding evidence that indicates a company's (and / or consortium’s) ability to successfully deliver the project described in the submission. 4) Allow Innovate UK to make the best use of its existing data by extracting data ‘signals’ - and connections between these signals - presented in an easy to understand graphical interface. This approach will surface insights and latent connections to help Innovate UK better understand their own data.
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国内基金
海外基金
Understanding structural evolution of galaxies with machine learning
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批准号:
-
项目类别:省市级项目
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资助金额:10.0万元
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批准年份:2022
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负责人:Nicola Rosario Napolitano
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依托单位:
非标准随机调度模型的最优动态策略
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批准号:71071056
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项目类别:面上项目
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资助金额:28.0万元
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批准年份:2010
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负责人:吴贤毅
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依托单位:
微生物发酵过程的自组织建模与优化控制
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批准号:60704036
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项目类别:青年科学基金项目
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资助金额:21.0万元
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批准年份:2007
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负责人:高学金
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依托单位: