TY - GEN
T1 - Personalized web service ranking via user group combining association rule
AU - Rong, Wenge
AU - Liu, Kecheng
AU - Liang, Lin
PY - 2009
Y1 - 2009
N2 - Web service plays an important role in implementing Service Oriented Architecture (SOA) for achieving dynamic business process. With the increased number of web services advertised in public repository, it is becoming vital to provide an efficient web service discovery and selection mechanism with respect to a user's requirement. Considerable efforts have been made to solve this problem among which semantic based web service discovery has been attained much importance by researchers in academic and industry community. However, there is a challenge in the semantic based web service discovery process, that is, among the retrieved set of semantically equivalent web service candidates, how to discern which one is the best? In this paper, inspired by collaborative filtering idea, a web service ranking framework is proposed in which a set of users with similar interest will be firstly identified. Afterwards, association rules will be found out by analyzing all web service composition transactions related to that set of users. By combining user group and association rule mined from that group, a personalized web service ranking mechanism is achieved and the experiment shows the promising result.
AB - Web service plays an important role in implementing Service Oriented Architecture (SOA) for achieving dynamic business process. With the increased number of web services advertised in public repository, it is becoming vital to provide an efficient web service discovery and selection mechanism with respect to a user's requirement. Considerable efforts have been made to solve this problem among which semantic based web service discovery has been attained much importance by researchers in academic and industry community. However, there is a challenge in the semantic based web service discovery process, that is, among the retrieved set of semantically equivalent web service candidates, how to discern which one is the best? In this paper, inspired by collaborative filtering idea, a web service ranking framework is proposed in which a set of users with similar interest will be firstly identified. Afterwards, association rules will be found out by analyzing all web service composition transactions related to that set of users. By combining user group and association rule mined from that group, a personalized web service ranking mechanism is achieved and the experiment shows the promising result.
KW - Association rule
KW - Personalization
KW - Ranking
KW - User group
KW - Web service selection
UR - https://www.scopus.com/pages/publications/70449559104
U2 - 10.1109/ICWS.2009.113
DO - 10.1109/ICWS.2009.113
M3 - 会议稿件
AN - SCOPUS:70449559104
SN - 9780769537092
T3 - 2009 IEEE International Conference on Web Services, ICWS 2009
SP - 445
EP - 452
BT - 2009 IEEE International Conference on Web Services, ICWS 2009
T2 - 2009 IEEE International Conference on Web Services, ICWS 2009
Y2 - 6 July 2009 through 10 July 2009
ER -