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Collective user behavior analysis for social intelligence

Collective user behavior analysis for social intelligence
社交智能的集体用户行为分析
批准号:
531376-2018
负责人:
Du, Weichang
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

项目摘要

项目成果

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中文摘要
翻译
该研究和开发项目的重点是社交媒体上的生活事件提及。我们的工作将主要集中在与生活事件预测有关的方面。虽然大量的研究都集中在多媒体内容,如图像和视频自动复述一系列的生活事件,很少有工作已经 ** 做在线社交网络中的流文本内容的生活事件预测的目的。这项任务 ** 具有挑战性,因为社交媒体帖子(如推文)具有简短、非正式和嘈杂的特点。此外,更重要的是,这项任务还存在“稀疏性问题”,因为社交媒体被生活事件以外的信息所主导。这一领域的研究已经有效地使用了各种类型的特征,包括 ** 社会交互,句法,语义和神经嵌入,以训练具有合理性能的分类器。该项目的目标是与行业合作伙伴ThinkCX密切合作,并开发一个多维框架,以探索如何根据流式社交文本内容预测生活事件。这将使工业合作伙伴能够构建工具,根据他们的生活事件更深入地了解 ** 用户的偏好和兴趣,从而提高客户满意度和客户参与度。该项目的成果将使行业合作伙伴能够微调其对最终用户的理解,从而有可能增加其客户群,从而增加收入 ** 并在加拿大雇用更多员工。
英文摘要
The focus of this research and development project is on life event mentions on social media. Our work will**focus primarily on aspects that relate to life event prediction. While a large body of research has focused on**multimedia content such as images and videos to automatically retell a series of life events, little work has been**done on streaming textual content in online social networks for the purposes of life event prediction. This task**is challenging due to the short, informal and noisy characteristics of social media posts such as tweets. Further**and more importantly, the task also suffers from the "sparsity problem," as social media is dominated by**information other than life events. Research in this area has effectively used various types of features including**social interaction, syntactic, semantic, and neural embeddings to train classifiers with reasonable performance.**The objective of this project will be to work in close collaboration with ThinkCX, the industrial partner, and to**develop a multidimensional framework for exploring how life events can be predicted based on streaming**social textual content. This will enable the industrial partner to build tools that gain deeper insight into the**users' preferences and interests based on their life events, resulting in higher customer satisfaction and**customer engagement. The outcomes of this project will enable the industry partner to fine-tune its**understanding of the end-users and hence potentially increase its customer base, leading to growth in revenue**and the hiring of more employees in Canada.
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Semantics based text matching for unstructured text documents
  • 批准号:
    508398-2017
  • 项目类别:
    Engage Plus Grants Program
  • 资助金额:
    $0.91万
  • 财政年份:
    2017
  • 负责人:
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Semantics based text matching for unstructured text documents
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  • 项目类别:
    Engage Grants Program
  • 资助金额:
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  • 财政年份:
    2016
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High-level programming paradigm for context-aware computing
  • 批准号:
    121667-2007
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
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    2014
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    453718-2013
  • 项目类别:
    Engage Grants Program
  • 资助金额:
    $1.82万
  • 财政年份:
    2013
  • 负责人:
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无线网络中多用户合作分集技术研究
  • 批准号:
    60472079
  • 项目类别:
    面上项目
  • 资助金额:
    25.0万元
  • 批准年份:
    2004
  • 负责人:
    仇佩亮
  • 依托单位: