As the age of ubiquitous commerce is upon us, personalization service is getting interested. Therefore, the recommendation methods that offer useful information to the customers become more important. However, most of them depend on a specific method and are restricted to the e-commerce. For applying these recommendation methods into U-commerce, first it is necessary that the extended context modeling and systematic connection of the methods to supplement some deficiency of each recommendation method. Therefore, we propose a modeling technique of context information related to personal activity in commercial transaction and show incremental preference analysis method, using preference tree which is closely connected to recommendation method in each step. And also, we use an XML indexing technique to efficiently extract the recommendation information from a preference tree.
|Title of host publication||International Workshop on Ubiquitous Data Management, 2005. UDM 2005|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Number of pages||8|
|Publication status||Published - 2005|