TY - GEN
T1 - Preference based recommendation method by SOM aided AHP and a case study of smartphone
AU - Zeng, Xuecong
AU - Cai, Longsheng
AU - Murata, Tomohiro
PY - 2012/11/1
Y1 - 2012/11/1
N2 - With the prosperity of e-commerce, the recommendation service rises rapidly due to its significant performance on promotion of consumer satisfaction level and sales. On one hand, it helps the consumer to find the suitable products in a much easier way. On the other, it explores the potential need of the consumer therefore steps up the deal. In order to make improvement on user stickiness, the recommendation system is now recognized as a vital role in intensive competition. However, it has an obvious weakness when helping consumers choose high-tech products where it requires much strict technical knowledge and it is not effective to recommend new products due to the lack of ratings. This research provides a new recommendation method related to high-tech products based on consumer's preference with less complexity and more effectiveness. It aims to make the new products equivalent to the old ones during the computing process therefore improve the effectiveness of new product recommendation.
AB - With the prosperity of e-commerce, the recommendation service rises rapidly due to its significant performance on promotion of consumer satisfaction level and sales. On one hand, it helps the consumer to find the suitable products in a much easier way. On the other, it explores the potential need of the consumer therefore steps up the deal. In order to make improvement on user stickiness, the recommendation system is now recognized as a vital role in intensive competition. However, it has an obvious weakness when helping consumers choose high-tech products where it requires much strict technical knowledge and it is not effective to recommend new products due to the lack of ratings. This research provides a new recommendation method related to high-tech products based on consumer's preference with less complexity and more effectiveness. It aims to make the new products equivalent to the old ones during the computing process therefore improve the effectiveness of new product recommendation.
KW - Analytic Hierarchy Process
KW - Self-organizing maps
KW - multi-criteria
KW - preference
KW - ranking
UR - http://www.scopus.com/inward/record.url?scp=84867932206&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867932206&partnerID=8YFLogxK
U2 - 10.1109/ICAL.2012.6308253
DO - 10.1109/ICAL.2012.6308253
M3 - Conference contribution
AN - SCOPUS:84867932206
SN - 9781467303620
T3 - IEEE International Conference on Automation and Logistics, ICAL
SP - 478
EP - 483
BT - 2012 IEEE International Conference on Automation and Logistics, ICAL 2012
T2 - 2012 IEEE International Conference on Automation and Logistics, ICAL 2012
Y2 - 15 August 2012 through 17 August 2012
ER -