SGER: Personalization by Partial Evaluation
SGER:通过部分评估实现个性化
基本信息
- 批准号:0136182
- 负责人:
- 金额:$ 5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2002
- 资助国家:美国
- 起止时间:2002-10-01 至 2004-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Information personalization refers to the automatic adjustment of information content, structure, and presentation tailored to an individual user. The goal of this research project is to develop a modeling methodology for information personalization. The methodology developed in this project termed PIPE ("Personalization is Partial Evaluation") makes no commitments to a particular personalization algorithm or format for information resources. Instead it emphasizes the representation of information systems in a way that allows their subsequent personalization. With this methodology, web sites and other information resources can be modeled and personalized for users' information-seeking goals. The specific activities conducted in this project include (1) characterizing the types of information systems for which this methodology is applicable and (2) constructing "personable" information system designs. The first activity is approached by defining how information systems are constructed and the representations they afford. The second activity involves the definition of a "personability" metric for evaluating information system designs. Human-computer interaction methodologies and systematic procedures for evaluation need to be enhanced to provide the needed input for the model formulation and validation. The results of this project will help define "personable information spaces" rigorously. With a formal model for personalization, we can design better information systems that can help users achieve their information-seeking goals.
信息个性化是指自动调整信息的内容、结构和表示,以适应个人用户。本研究项目的目标是为信息个性化开发一种建模方法。在这个项目中开发的称为PIPE(“个性化是部分评估”)的方法没有对信息资源的特定个性化算法或格式做出承诺。相反,它强调以一种允许其后续个性化的方式表示信息系统。利用这种方法,可以对网站和其他信息资源进行建模和个性化,以满足用户的信息寻求目标。在这个项目中进行的具体活动包括(1)描述这种方法适用的信息系统的类型,以及(2)构建“个性化”的信息系统设计。第一项活动是通过定义如何构建信息系统及其提供的表示来实现的。第二个活动涉及评估信息系统设计的“个性”度量的定义。需要加强人机交互方法和系统的评价程序,以便为模型的制定和验证提供所需的输入。这个项目的结果将有助于严格定义“个性化信息空间”。有了一个正式的个性化模型,我们就可以设计出更好的信息系统,帮助用户实现他们的信息搜索目标。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Naren Ramakrishnan其他文献
Protein Design by Sampling an Undirected Graphical Model of Residue Constraints
通过对残基约束的无向图形模型进行采样进行蛋白质设计
- DOI:
10.1109/tcbb.2008.124 - 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
John Thomas;Naren Ramakrishnan;C. Bailey - 通讯作者:
C. Bailey
Reconstructing chemical reaction networks: data mining meets system identification
重构化学反应网络:数据挖掘遇上系统识别
- DOI:
10.1145/1401890.1401912 - 发表时间:
2008 - 期刊:
- 影响因子:0
- 作者:
Y. Cho;Naren Ramakrishnan;Yang Cao - 通讯作者:
Yang Cao
Forecasting Rare Disease Outbreaks with Spatio-temporal Topic Models
使用时空主题模型预测罕见疾病爆发
- DOI:
- 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
Saurav Ghosh;Theodoros Rekatsinas;S. Mekaru;E. Nsoesie;J. Brownstein;L. Getoor;Naren Ramakrishnan - 通讯作者:
Naren Ramakrishnan
(Hyper) local news aggregation: designing for social affordances
(超级)本地新闻聚合:针对社会可供性进行设计
- DOI:
10.1145/2307729.2307736 - 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Andrea L. Kavanaugh;Ankit Ahuja;S. Gad;S. Neidig;Manuel A. Pérez;Naren Ramakrishnan;J. Tedesco - 通讯作者:
J. Tedesco
A Nonparametric Approach to Uncovering Connected Anomalies by Tree Shaped Priors
通过树形先验发现关联异常的非参数方法
- DOI:
10.1109/tkde.2018.2868097 - 发表时间:
2019-10 - 期刊:
- 影响因子:0
- 作者:
Nannan Wu;Feng Chen;Jianxin Li;Jin-Peng Huai;Baojian Zhou;Bo Li;Naren Ramakrishnan - 通讯作者:
Naren Ramakrishnan
Naren Ramakrishnan的其他文献
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{{ truncateString('Naren Ramakrishnan', 18)}}的其他基金
D-ISN/Collaborative Research: Machine Learning to Improve Detection and Traceability of Forest Products using Stable Isotope Ratio Analysis (SIRA)
D-ISN/合作研究:利用稳定同位素比率分析 (SIRA) 提高林产品检测和可追溯性的机器学习
- 批准号:
2240402 - 财政年份:2023
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
Expeditions: Collaborative Research: Global Pervasive Computational Epidemiology
探险:合作研究:全球普适计算流行病学
- 批准号:
1918770 - 财政年份:2020
- 资助金额:
$ 5万 - 项目类别:
Continuing Grant
NRT-DESE: UrbComp: Data Science for Modeling, Understanding, and Advancing Urban Populations
NRT-DESE:UrbComp:用于建模、理解和促进城市人口发展的数据科学
- 批准号:
1545362 - 财政年份:2015
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
Formal Models, Algorithms, and Visualizations for Storytelling Analytics
用于讲故事分析的形式模型、算法和可视化
- 批准号:
0937133 - 财政年份:2009
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
III: Medium: Collaborative Research: Integration, Prediction, and Generation of Mixed Mode Information using Graphical Models, with Applications to Protein-Protein Interactions
III:媒介:协作研究:使用图形模型整合、预测和生成混合模式信息,并应用于蛋白质-蛋白质相互作用
- 批准号:
0905313 - 财政年份:2009
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
CSR-AES: The Adaptive Code Kitchen: Flexible Approaches to Dynamic Application Composition
CSR-AES:自适应代码厨房:动态应用程序组合的灵活方法
- 批准号:
0615181 - 财政年份:2006
- 资助金额:
$ 5万 - 项目类别:
Continuing Grant
NGS: A Microarray Experiment Management System
NGS:微阵列实验管理系统
- 批准号:
0103660 - 财政年份:2001
- 资助金额:
$ 5万 - 项目类别:
Continuing Grant
CAREER: Runtime Recommender Systems for Compositional Modeling of Scientific Computations
职业:用于科学计算组合建模的运行时推荐系统
- 批准号:
9984317 - 财政年份:2000
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
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