Important User Group Based Web Service Recommendation

Abstract

Due to the burgeoning of online services, web service recommendation system (WSRS) has received extensive attention no matter in the academia or industry. As an effective personalization technique, it solicits recommendations from one another and recommends appropriate services to target users. However, with the advent of shilling attack, problems arise along with the rapid development of such promising technology, which is, the existence of noisy attacking profiles leads to the inaccuracy of recommendation results. Since current state-of-the-art approaches rarely take such security aspects into consideration, we propose a novel recommending framework based on Important User Group (IUG) incorporating traditional collaborative filtering algorithm to achieve a robust web service recommendation. In our work, three selection methods are applied to obtain IUG, eliminating certain quantity of malicious users. Experimental results on Meizu-AppCom, WS-DREAM, and Epinions demonstrate resilience of IUG to shilling attacks.