EAGER: The Virtual Assistant Health Coach: Summarization and Assessment of Goal-Setting Dialogues

EAGER：虚拟助理健康教练：目标设定对话的总结和评估

• 批准号: 1650900
• 负责人: Brian Ziebart
• 金额: $ 29.99万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1650900&HistoricalAwards=false
• 关键词: EAGER; Virtual; Assistant; Health; Coach

Health coaching is an effective process for improving poor health behaviors by providing education on health-related topics, setting personalized and realizable health-related goals, monitoring and encouraging progress towards those goals, and sequencing or refining a progression of health goals over time. Though useful, its highly personalized and labor-intensive nature makes the cost of effective health coaching prohibitive for many underserved populations that could benefit significantly from it. This EArly Grant for Exploratory Research (EAGER) seeks to conduct an exploratory investigation of the technical feasibility of creating a virtual health coaching system that learns from expert demonstration to interact with patients via the smart message system (SMS). The project develops two key initial components: a health goal summarization component that extracts details of proposed and agreed upon health goals from SMS dialogues between participant and health coach; and a health goal assessment component that estimates the suitability of proposed health goals in terms of the five dimensions of goal setting used by the coaching experts: Specificity, Measurability, Attainability, Relevance, and Timeliness (SMART).This EAGER project develops techniques to interpret short, telegraphic, and often ungrammatical SMS messages and to extract details of health goals for improving physical activities established in those messages using natural language processing and structured prediction methods. It expands sentiment analysis methods to identify both noun and non-noun targets of emotion and uses these analyses in combination with inverse optimal control methods to assess the suitability of the sequence of proposed health goals over the course of the dialogue in terms of each of the five SMART dimensions. Evaluation of the developed methods is planned using a collected corpus of SMS-based communications between a health coach and participants annotated with tags relating to semantics, sentiments, and health goals. Successful development of these capabilities represent an important first step for realizing a virtual health coaching system that is able to provide personalized health coaching benefits of comparable quality to a human health coach.

健康指导是一个有效的过程，通过提供健康相关主题的教育，设定个性化和可实现的健康相关目标，监测和鼓励实现这些目标的进展，以及随着时间的推移对健康目标的进展进行排序或细化，来改善不良健康行为。虽然有用，它的高度个性化和劳动密集型的性质使得有效的健康教练的成本高昂，许多服务不足的人群，可以从中受益显着。EARLY探索性研究资助（EAGER）旨在进行探索性调查的技术可行性，创建一个虚拟的健康教练系统，从专家演示学习，通过智能消息系统（SMS）与患者互动。该项目开发了两个关键的初始组件：健康目标总结组件，从参与者和健康教练之间的SMS对话中提取拟议和商定的健康目标的细节;以及健康目标评估组件，根据教练专家使用的目标设定的五个维度估计拟议健康目标的适用性：具体性，可测量性，可实现性，相关性和及时性（SMART）。EAGER项目开发了解释简短，电报，以及通常不合语法的SMS消息，并提取用于改善在这些消息中建立的身体活动的健康目标的细节，语言处理和结构化预测方法。它扩展了情感分析方法，以确定情感的名词和非名词目标，并使用这些分析与逆最优控制方法相结合，以评估在对话过程中提出的健康目标的序列的适合性，在每个方面的五个SMART维度。评估开发的方法计划使用收集的语料库的基于SMS的通信之间的健康教练和参与者注释与语义，情绪和健康目标的标签。这些能力的成功开发代表了实现虚拟健康教练系统的重要的第一步，该虚拟健康教练系统能够提供与人类健康教练质量相当的个性化健康教练益处。

项目成果

Sentiment Lexicon Expansion Based on Neural PU Learning, Double Dictionary Lookup, and Polarity Association

• DOI: 10.18653/v1/d17-1059
• 发表时间: 2017-09
• 作者: Yasheng Wang;Yang Zhang;Bing Liu

Lifelong Learning CRF for Supervised Aspect Extraction

• DOI: 10.18653/v1/p17-2023
• 发表时间: 2017-04
• 作者: Lei Shu;Hu Xu;B. Liu

Towards Building a Virtual Assistant Health Coach

建立虚拟助理健康教练

• DOI: 10.1109/ichi.2018.00081
• 发表时间: 2018
• 期刊: IEEE International Conference on Healthcare Informatics (ICHI
• 作者: Gupta, Itika;Di Eugenio, Barbara;Ziebart, Brian;Liu, Bing;Gerber, Ben;Sharp, Lisa;Davis, Rafe;Baiju, Aiswarya
• 通讯作者: Baiju, Aiswarya

Target-Sensitive Memory Networks for Aspect Sentiment Classification

• DOI: 10.18653/v1/p18-1088
• 发表时间: 2018-07
• 作者: Shuai Wang;S. Mazumder;B. Liu;Mianwei Zhou;Yi Chang