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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
这个研发项目的重点是社交媒体上提到的生活事件。我们的工作将**主要集中在与生活事件预测有关的方面。虽然大量的研究集中在**图像和视频等多媒体内容上,以自动复述一系列生活事件,但在在线社交网络中用于预测生活事件的流媒体文本内容方面的工作还很少。由于推文等社交媒体帖子的简短、非正式和嘈杂的特点,这项任务**具有挑战性。此外,更重要的是,这项任务还存在“稀疏性问题”,因为社交媒体上充斥着生活事件以外的信息。这一领域的研究已经有效地利用了各种类型的功能,包括**社交互动、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,探索如何基于流媒体**社交文本内容预测生活事件。这将使行业合作伙伴能够构建工具,根据**用户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。该项目的结果将使行业合作伙伴能够微调其对最终用户的**了解,从而潜在地增加其客户基础,从而导致收入**的增长**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
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  • 项目类别:
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  • 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
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    Engage Grants Program
  • 资助金额:
    $1.82万
  • 财政年份:
    2013
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国内基金
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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
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