TY - GEN
T1 - Adaptive user interface agent for personalized public transportation recommendation system
T2 - 17th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2014
AU - Nakamura, Hiroyuki
AU - Gao, Yuan
AU - Gao, He
AU - Zhang, Hongliang
AU - Kiyohiro, Akifumi
AU - Mine, Tsunenori
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2014.
PY - 2014
Y1 - 2014
N2 - Public transportation guidance services, which are widely used nowadays, support our daily lives. However they have not fully been personalized yet. Regarding personalized services, an adaptive user interface plays a crucial role. This paper presents an Adaptive User Interface (AUI) agent of our personalized transportation recommendation system called PATRASH. To design and implement the agent, first, we collected and analyzed public transportation usage histories of 10 subjects so as to confirm the possibilities and effectiveness of the personalized route recommendation function. Then we propose a method to deal with user histories and evaluate the effectiveness of the proposed method based on click costs, comparing with two major transportation guidance systems in Japan. We also propose a decision-tree-based route recommendation method. The experimental results illustrate the effectiveness of the proposed method.
AB - Public transportation guidance services, which are widely used nowadays, support our daily lives. However they have not fully been personalized yet. Regarding personalized services, an adaptive user interface plays a crucial role. This paper presents an Adaptive User Interface (AUI) agent of our personalized transportation recommendation system called PATRASH. To design and implement the agent, first, we collected and analyzed public transportation usage histories of 10 subjects so as to confirm the possibilities and effectiveness of the personalized route recommendation function. Then we propose a method to deal with user histories and evaluate the effectiveness of the proposed method based on click costs, comparing with two major transportation guidance systems in Japan. We also propose a decision-tree-based route recommendation method. The experimental results illustrate the effectiveness of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=84910137084&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84910137084&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-13191-7_19
DO - 10.1007/978-3-319-13191-7_19
M3 - Conference contribution
AN - SCOPUS:84910137084
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 238
EP - 245
BT - PRIMA 2014
A2 - Dam, Hoa Khanh
A2 - Pitt, Jeremy
A2 - Xu, Yang
A2 - Governatori, Guido
A2 - Ito, Takayuki
PB - Springer Verlag
Y2 - 1 December 2014 through 5 December 2014
ER -