Title :
A Hybrid Framework for Building a Web-Page Recommender System
Author :
Anastopoulos, Vasileios ; Karampelas, Panagiotis ; Kalagiakos, Panagiotis ; Alhajj, Reda
Author_Institution :
Hellenic American Univ., NH, USA
Abstract :
Recommender systems aim to facilitate World Wide Web users against information and product overloading. They are usually intermediate programs that try to predict users´ preferences and items of their interest. In this paper, we present a hybrid framework that uses open source information such as web logs in combination with social network analysis and data mining, to extract useful information about users browsing patterns and construct a recommendation engine. A case study based on real data from an organization of 250 employees is presented and a system prototype is constructed based on the results.
Keywords :
Internet; data mining; information retrieval; recommender systems; social networking (online); Web logs; Web-page recommender system; World Wide Web; data mining; information extraction; information overloading; open source information; product overloading; recommendation engine; social network analysis; Association rules; IP networks; Itemsets; Recommender systems; Social network services; Web pages; association rules; data mining; hybrid framework; recommender system; social network; system prototype;
Conference_Titel :
Intelligence and Security Informatics Conference (EISIC), 2011 European
Conference_Location :
Athens
Print_ISBN :
978-1-4577-1464-1
Electronic_ISBN :
978-0-7695-4406-9
DOI :
10.1109/EISIC.2011.40
