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Fuzzy prototype model and semantic distance

机译:模糊原型模型与语义距离

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摘要

It is a challenge to provide an intelligent product suggestion for these new customers without previous shopping records in the supermarket application. To solve such a problem, we design a hybrid fuzzy expert system for recommendation using the improved fuzzy prototype model and semantic distance. Moreover, we implement a demonstration of the recommendation system by using intelligent Fril/SQL interrogator, which is an object-oriented and knowledge-based support query system containing the set of reusable logic objects linking one another. The results are evaluated by comparing the average product frequency of recommendations with the average frequency of non-recommendations.
机译:在没有超级市场应用程序先前购物记录的情况下为这些新客户提供智能产品建议是一项挑战。为了解决这个问题,我们使用改进的模糊原型模型和语义距离设计了一个混合的模糊专家系统进行推荐。此外,我们通过使用智能Fril / SQL询问器来实现推荐系统的演示,该询问器是一个面向对象的基于知识的支持查询系统,其中包含一组相互链接的可重用逻辑对象。通过比较建议的平均产品频率和不推荐的平均频率来评估结果。

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