Mining Association Rule on Service Data using Frequency and Weight
Jeong Hee Hwang · Journal of Digital Contents Society · 2016
The general frequent pattern mining considers frequency and support of items.To extract useful information, it is necessary to consider frequency and weight of items that reflects the changing of user interest as time passes.The suitable services considering time or location is requested by user so that the weighted mining method is necessary.We propose a method of weighted frequent pattern mining based on service ontology.The weight considering time and location is given to service items and it is applied to association rule mining method.The extracted rule is combined with stored service rule and it is based on timely service to offer for user.