Ontology-based personalized couple clustering for heterogeneous product recommendation in mobile marketing

摘要

Plethora of cellular phones has been increasingly driving the spread of e-commerce mechanisms running on mobile devices. For instance, mobile marketing fulfills the wireless delivery (to the devices of mobile users) of the recommended product information and even one-to-one recommendations. One-to-one recommendation not only reduces the time that customers have to expend to for attaining appropriate products, but also is a method to engender customer values and develop the long-term customer relationships. This paper presents a one-to-one recommendation mechanism that iteratively takes as inputs the audio customer messages (together with product information) and produces personalized product analogy structures (that subsequently drive the generation of personalized heterogeneous product recommendations) based on the coupled clustering algorithm. The personalized product analogy structures also evolve as the messages (of the correspondent customer) grow. We have implemented the mechanism with J2EE Web Service that has produced fairly promising evaluation results.