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CARE-RATE: An AI-based dynamic online information filtering system

CARE-RATE: An AI-based dynamic online information filtering system
CARE-RATE:基于人工智能的动态在线信息过滤系统
批准号:
555659-2020
负责人:
Boger, Jennifer
金额:
$1.09万
依托单位:
依托单位国家:
加拿大
项目类别:
Idea to Innovation
财政年份:
2020
资助国家:
加拿大
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31
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英文摘要
Waterloo's Dialog & AI Based Search Engine Software (also called CARE-RATE) is a novel cloud-based software is developed through user-centred design approaches (i.e. involvement from targeted primary users). It employs natural language processing and deep learning such that an end user will have a Q & A type dialogue with the system to capture a problem he/she is encountering as well as relevant contextual information. The software system uses this information to perform a search, filter, and rank results of relevant online resources that complement the user's specific context. It can learn "meta-data" on websites relevant to user needs (e.g. if a user needs information on financial planning, an appropriate set of documents will be curated with that particular criterion). Users will be able to rate the "usefulness" of results, enabling the system to autonomously learn over time, improving future searches and results. Current competitive search engines rely on personalized search or long-term search histories and generate large amounts of (mainly) irrelevant information, particularly in cases where the system at hand is unable to gather users' historical search history or the user' intent is obscured by an inadequate vocabulary. Advantage of Waterloo's technology include: (1) better search results by pro-actively adapting search results to the needs of the user (2) software learns "meta-data" on websites relevant to user needs (3) semi-supervised learning (i.e. user rating of search results) enables system to perform progressively better searches. This innovation has applications in most industries including advertising, e-commerce, education, etc. Enterprises in these industries face the challenge of having large sets of data while lacking comprehensive automated search systems and are unable to extract highly relevant content based on users' queries or keyword inputs. Examples of other use cases include database mining, internal proprietary data searches particularly where there are complex technical terms or meta-data (e.g. law firms, medical and pharmaceutical industries).
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Zero-effort ambient vitals monitoring
  • 批准号:
    RGPIN-2018-04716
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2021
  • 负责人:
    Boger, Jennifer
  • 依托单位:
Zero-effort ambient vitals monitoring
  • 批准号:
    RGPIN-2018-04716
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2020
  • 负责人:
    Boger, Jennifer
  • 依托单位:
Zero-effort ambient vitals monitoring
  • 批准号:
    RGPIN-2018-04716
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2019
  • 负责人:
    Boger, Jennifer
  • 依托单位:
Zero-effort ambient vitals monitoring
  • 批准号:
    DGECR-2018-00263
  • 项目类别:
    Discovery Launch Supplement
  • 资助金额:
    $0.91万
  • 财政年份:
    2018
  • 负责人:
    Boger, Jennifer
  • 依托单位:
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