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Crossover Method for Interactive Genetic Algorithms to Estimate Multimodal Preferences

机译:交互式遗传算法估计多峰偏好的交叉方法

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摘要

We apply an interactive genetic algorithm (iGA) to generate product recommendations. iGAs search for a single optimum point based on a user's Kansei through the interaction between the user and machine. However, especially in the domain of product recommendations, there may be numerous optimum points. Therefore, the purpose of this study is to develop a new iGA crossover method that concurrently searches for multiple optimum points for multiple user preferences. The proposed method estimates the locations of the optimum area by a clustering method and then searches for the maximum values of the area by a probabilistic model. To confirm the effectiveness of this method, two experiments were performed. In the first experiment, a pseudouser operated an experiment system that implemented the proposed and conventional methods and the solutions obtained were evaluated using a set of pseudomultiple preferences. With this experiment, we proved that when there are multiple preferences, the proposed method searches faster and more diversely than the conventional one. The second experiment was a subjective experiment. This experiment showed that the proposed method was able to search concurrently for more preferences when subjects had multiple preferences.
机译:我们应用交互式遗传算法(iGA)生成产品推荐。 iGA通过用户与机器之间的交互,根据用户的Kansei搜索单个最佳点。但是,特别是在产品推荐方面,可能存在许多最佳点。因此,本研究的目的是开发一种新的iGA交叉方法,该方法可以同时搜索多个用户偏好的多个最佳点。提出的方法通过聚类方法估计最佳区域的位置,然后通过概率模型搜索区域的最大值。为了确认该方法的有效性,进行了两个实验。在第一个实验中,一个伪用户操作了一个实验系统,该系统实施了建议的和常规的方法,并使用一组伪多重首选项对获得的解决方案进行了评估。通过该实验,我们证明了当存在多个偏好时,所提出的方法比传统方法搜索得更快,更多样化。第二个实验是主观实验。该实验表明,当受试者具有多个偏好时,所提出的方法能够同时搜索更多的偏好。

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  • 来源
    《Applied computational intelligence and soft computing》 |2013年第2013期|302573.1-302573.16|共16页
  • 作者单位

    Graduate School of Engineering, Doshisha University, 1-3 Tatara Miyakodani, Kyotanabe-shi, Kyoto 610-0394, Japan;

    Kanazawa Seiryo University Women's Junior College, 10-1 Ushi, Gosho-machi, Kanazawa-shi, Ishikawa 920-8620, Japan;

    Faculty of Science and Engineering Doshisha University, 1-3 Tatara Miyakodani, Kyotanabe-shi, Kyoto 610-0394, Japan;

    Faculty of Life and Medical Sciences, Doshisha University, 1-3 Tatara Miyakodani, Kyotanabe-shi, Kyoto 610-0394, Japan;

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