Question Recommendation Based on User Model in CQA

2017 ◽  
pp. 91-101
Author(s):  
Junfeng Wang ◽  
Lei Su ◽  
Jun Chen ◽  
Di Jiang
Keyword(s):  
User Model ◽  
Question Recommendation

Spoken Natural Language Dialog Systems

1995 ◽  
Author(s):  
Ronnie W. Smith ◽  
D. Richard Hipp
Keyword(s):  
Problem Solving ◽  
Natural Language ◽  
Error Correction ◽  
User Model ◽  
Dialog Systems ◽  
Problem Solving Process ◽  
Processing Architecture ◽  
Dialog Processing

As spoken natural language dialog systems technology continues to make great strides, numerous issues regarding dialog processing still need to be resolved. This book presents an exciting new dialog processing architecture that allows for a number of behaviors required for effective human-machine interactions, including: problem-solving to help the user carry out a task, coherent subdialog movement during the problem-solving process, user model usage, expectation usage for contextual interpretation and error correction, and variable initiative behavior for interacting with users of differing expertise. The book also details how different dialog problems in processing can be handled simultaneously, and provides instructions and in-depth result from pertinent experiments. Researchers and professionals in natural language systems will find this important new book an invaluable addition to their libraries.

An Empirical Case Study of Factor Alignment Problems Using the USER Model

2012 ◽  
Vol 21 (1) ◽  
pp. 25-43 ◽  
Author(s):  
Anureet Saxena ◽  
Robert A. Stubbs
Keyword(s):  
User Model

scholarly journals Adaptive Health Coaching Technology for Tailored Interventions

2021 ◽  
Vol 18 (5) ◽  
pp. 2761
Author(s):  
Holly Jimison ◽  
Michael Shapiro ◽  
Misha Pavel
Keyword(s):  
Older Adults ◽  
Chronic Conditions ◽  
User Model ◽  
Health Coaching ◽  
Communications Technology ◽  
Message Content ◽  
Tailored Interventions ◽  
Age In Place ◽  
Health Coaches ◽  
Scalable Methods

Recent advances in sensor and communications technology have enabled scalable methods for providing continuity of care to the home for patients with chronic conditions and older adults wanting to age in place. In this article we describe our framework for a health coaching platform with a dynamic user model that enables tailored health coaching messages. We have shown that this can improve coach efficiency without a loss of message quality. We also discovered many lessons for coaching technology, most demonstrating the need for more coach input on sample message content, perhaps even requiring that individual coaches be able to modify the message database directly. Overall, coaches felt that the structure of the automated message generation was useful in remembering what to say, easy to edit if necessary and especially helpful for training new health coaches.

scholarly journals Joint Implicit and Explicit Neural Networks for Question Recommendation in CQA Services

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 73081-73092 ◽  
Author(s):  
Hongkui Tu ◽  
Jiahui Wen ◽  
Aixin Sun ◽  
Xiaodong Wang
Keyword(s):  
Neural Networks ◽  
Question Recommendation ◽  
Implicit And Explicit
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