A dual-layer user model based cognitive system for user-adaptive service robots

2011 RO-MAN ◽  
2011 ◽  
Author(s):  
Seong-Yong Koo ◽  
Kiru Park ◽  
Hyun Kim ◽  
Dong-Soo Kwon
Keyword(s):  
User Model ◽  
Cognitive System ◽  
Service Robots ◽  
Model Based

Model-Based Development with User Model as Practical Process of HCD for Developing Robots

2016 ◽  
Vol 28 (4) ◽  
pp. 579-590 ◽  
Author(s):  
Yoshinobu Akimoto ◽  
◽  
Eri Sato-Shimokawara ◽  
Yasunari Fujimoto ◽  
Toru Yamaguchi
Keyword(s):  
Development Process ◽  
User Model ◽  
Service Robots ◽  
Service Robot ◽  
Human Beings ◽  
Human Centered Design ◽  
Model Based ◽  
Telepresence Robot ◽  
Text Model ◽  
Quality In Use

[abstFig src='/00280004/15.jpg' width='300' text='Model-based development with user model' ] The service robots now common in daily life are expected to provide highly useful services with high usability and high user experience (UX) to users and human beings around the service robots. Human-centered design (HCD) became used in a variety of industries, and HCD will be required in the service robot industry for improving usability and UX. However, no practical process of HCD has, to our knowledge, been proposed for service robots. So, we have been studying a development process for the service robots to improve a quality in use – a process we call model-based development with user models (MBD/UM). We certified the possibility of MBD/UM as a practical process of HCD by applying MBD/UM to approach function research on a telepresence robot.

A Personalized Recommendation Model Based on Contextual Information

2015 ◽  
Vol 713-715 ◽  
pp. 1530-1533
Author(s):  
Yuan Zi He
Keyword(s):  
Recommender System ◽  
Information Overload ◽  
Contextual Information ◽  
User Model ◽  
Personalized Recommendation ◽  
Contextual Data ◽  
Model Based ◽  
Structure Text ◽  
Novel Model

Personalized recommendation offers a new way to solve the problem of information overload. In order to effectively build user model and improve the effect of personalized recommendation, this paper proposes a novel model for mining contextual information of non-structure text, and insects the contextual information into user model, which enriches user model. The experiment results shown that the model can greatly improve the recommendation performance when the model is applied to contextual data of the recommender system in hotel.

The Building of User Model of Personalized Learning Teaching System Based on Data Mining

2013 ◽  
Vol 756-759 ◽  
pp. 2047-2050
Author(s):  
Wen Yan Rui ◽  
Hai Ying Mi
Keyword(s):  
Data Mining ◽  
User Behavior ◽  
Relevant Information ◽  
Personalized Learning ◽  
User Model ◽  
Teaching System ◽  
Individual User ◽  
Model Based

This paper analyzes the structure of the whole system, namely, how different users according to their own characteristics of its initiative to provide users with relevant information and content and to establish individual user model, based on user behavior to build personalized user model.

Design and Implementation of User Model Based on Light Blog

2014 ◽  
Vol 556-562 ◽  
pp. 6003-6006
Author(s):  
Pei Pei Song ◽  
Yu Ming Qi ◽  
Zhong Min Wang
Keyword(s):  
Data Mining ◽  
User Model ◽  
Business Logic ◽  
Data Mining Technique ◽  
Design And Implementation ◽  
Mining Technique ◽  
Model Based ◽  
Model Similarity ◽  
Social Intercourse

Social intercourse based on interest is becoming more and more popular, design of the existing architecture and the business logic of the light blog by taking analysis is implemented. Through recording and analyzing users’ behavior and data profiles, this system can automatically push the new useful information to the specific users who may have an interest on that by data mining. In this paper, the application of the data mining technique, the implementation of TF-IDF algorithm and the solution of the model similarity are mainly explained.

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