Research on a Novel Interactive Immune Evolutionary Algorithm for Online Apparel Purchase Recommendation

The online-sales channel for apparel has become an outstanding channel for apparel industry and the online apparel purchase recommendation is challenging the traditional recommender systems. In this paper, the essential properties of online apparel purchase recommendation are analyzed and the problems of online apparel purchase recommendation are concluded as a kind of hybrid-indices optimization problems. To solve this kind of problems, a novel interactive immune evolutionary algorithm (IIEA) is proposed which is designed by integrating the interactive decision-making mechanism of interactive evolutionary computation (IEC) and the immune computing techniques. The simulation experiments for the online apparel purchase recommendation show that IIEA is effective and can efficiently alleviate the user fatigue problem.