Paper Info
Title
Towards Integrative Personal Character Modeling Using Multi-strategy Fusion Across Scenarios and Periods
Abstract
The individual-like intelligent artifact is a special humanoid, which resembles a real human being in terms of appearance, behavior, and characteristics. Such intelligent artifacts can help achieving numerous fantastic applications, including better-personalized services and digital immortality. Currently, limited progress has been made in recognizing personal inner characteristics. As a comprehensive description of an individuals' characteristics, the personal character model (PCM) is the key to individual-like intelligent artifacts. Based on personality and differential psychology, the proposed PCM consists of personal characteristics in affect, behavior and cognition (ABC), personality (P), and their relations (R). In this paper, three properties of PCM in terms of scenario and period are summarized. More specifically, the original PCM couldn't be calculated accurately and comprehensively given only one single scenario and a certain temporal period. An integrative personal character modeling is proposed on the basis of multistrategy fusion, which features accurate strategy fusion and comprehensive strategy fusion. These two fusion strategies are used to further improve the results of personal characteristics computed from various scenarios and different periods of time, so as to obtain a more accurate and more comprehensive PCM. Furthermore, the experimental categories and evaluation methods in personal character modeling are discussed and clarified in the current and future study.
Year
DOI
Venue
2019
10.1109/DASC/PiCom/CBDCom/CyberSciTech.2019.00043
2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)
Keywords
Field
DocType
Personal-Character-Model,Integrative-Modeling,Multi-Strategy-Fusion,Personality,Scenario,Period
Differential psychology,Computer science,Fusion,Artificial intelligence,Cognition,Big data,Machine learning,Personality
Conference
ISBN
Citations 
PageRank 
978-1-7281-3025-5
1
0.36
References 
Authors
6
3
Name
Order
Citations
PageRank
Ao Guo173.52
Jianhua Ma21401148.82
Kevin I-Kai Wang316729.65