Dynamic Recommendation System using Type of Web Document and Associated Documents

초록

Because web documents become creation and disappearance rapidly, users require the recommend system that offers users to browse the web document conveniently and correctly. In this paper, we propose the Recommendation system that classifies these web documents using similarity value between the web documents under the web document type and extracts the user browsing sequential pattern DB using users' session information based on the web server log files. When user accesses the web document, the proposed Dynamic recommendation system(DRS) recommends the associated web documents set that has high similarity document between current web document and other web documents in the same class and has sequential specificity using the extracted information and users' session information.