课题基金 / 基金详情

User Models for Intelligent Interfaces

User Models for Intelligent Interfaces
智能接口的用户模型
批准号:
9252825
负责人:
Loretta Moore
金额:
$1.2万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1993
资助国家:
美国
项目状态:
已结题
起止时间:
1993-02-15 至 1994-07-31

项目摘要

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中文摘要
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英文摘要
This is a one year MRIA planning grant award. The project consists of investigating the feasibility of research on intelligent interfaces based on a user behavior model which emphasizes individual user differences. Previous user models have been based on the similarities of the ideal, well-trained user. A secondary objective of the plan to be investigated is the use of the main results in the area of querying databases, particularly in aiding the user in the formation of queries. Finally, the project involves planning on the best approach for an evaluation of the system through testing with actual users of the system. This investigation contributes to the understanding of user models and their utility and, in general, to the theory and practice of interface design. The preliminary study investigates the most appropriate architecture for the adaptive user model, the design of the intelligent interface, and the evaluation study.
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New IPA assignment
  • 批准号:
    1823013
  • 项目类别:
    Intergovernmental Personnel Award
  • 资助金额:
    $21.86万
  • 财政年份:
    2018
  • 负责人:
    Loretta Moore
  • 依托单位:
I-Corps: Career Advancement for STEM Faculty through Summer Writing Retreats and Online Communities
  • 批准号:
    1519704
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    2015
  • 负责人:
    Loretta Moore
  • 依托单位:
EAGER: Advancing Computational Thinkers and Computing Innovators in a Cyber-Enabled Community
  • 批准号:
    1062118
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2010
  • 负责人:
    Loretta Moore
  • 依托单位:
Transforming the Climate and Advancing STEM Women at JSU, an HBCU in the South (JSUAdvance)
  • 批准号:
    1008708
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $357.11万
  • 财政年份:
    2010
  • 负责人:
    Loretta Moore
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
新型手性NAD(P)H Models合成及生化模拟