Application of Half-Life Theory and Fuzzy Theory to a Selection And Recommendation System for Web Advertisement Delivery In Consideration of the Time Effect

With the rapid development of the Internet, Web marketing has become more and more popular among businesses. However, excessive advertisement information is not only a burden to consumers but also a waste of marketing efforts. In this study, a personalized Web advertisement selection and recommendation system is proposed through a membership-based advertisement marketing website whose advertisement content is determined by consumer preference. As consumer preference declines with time, which is called the time effect, the proposed system applies the half-life theory and the fuzzy theory to members’ browsing behaviors and automatically analyzes browsers’ time-affected preference levels associated with the advertised products. Then, the target markets of the advertisement suppliers’ products are matched with customer preference so as to filter out a portfolio of candidate advertisements for delivery. Finally, advertisement delivery is arranged via a commercial advertisement delivery scheduling and recommendation model so that browsers obtain exactly the advertisements they need, the benefits of target marketing are increased, and Web advertising service providers’ market competitiveness is strengthened. Thus, a win-win-win scenario for the consumers, the advertisement suppliers, and the Web advertising service providers is realized.