SCIS & ISIS 2008という国際会議が名古屋で開催される．
Discussion on a Crossover Method using Probabilistic Model for interactive Genetic
In this research, we considered applying interactive Genetic Algorithm (iGA) to a product recommendation system. Products that suit a user’s preference can be presented by applying iGA to the system and learning the user’s preference. However, if the user’s preference is biased, the dependency among design variables should be considered. For this reason, we proposed an offspring generation with consideration for this dependency. In the proposed method, first we apply a clustering technique to the archived individuals which a user selected, and then we construct a Probabilistic Model based on that result in crossover. We plan on examining the effectiveness of the proposed mechanisms by experimenting with iGA for selecting colors and figures of symbols.