Towards a hybrid approach of Primitive Cognitive Network Process and Self-Organizing Map for computer product recommendation

Vincent Qi Chen, K. Yuen
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引用次数: 1

Abstract

Products have similarities which can be analyzed to recommend products to consumers with different preferences. This paper combines Primitive Cognitive Network Process (PCNP) and Self-Organizing Map (SOM) to cluster products into appropriate categories on the basis of consumer preferences and product similarities. PCNP is an ideal alternative of Analytic Hierarchy Process (AHP) to quantify the weights for the attributes used in SOM. To demonstrate the applicability of PCNP-SOM, an example of computer product recommendation is illustrated.
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基于原始认知网络过程和自组织映射的计算机产品推荐混合方法研究
产品具有相似性,可以通过分析相似性向不同偏好的消费者推荐产品。本文将原始认知网络过程(PCNP)和自组织映射(SOM)相结合,根据消费者偏好和产品相似度将产品聚类到适当的类别中。PCNP是层次分析法(AHP)的理想替代方案,用于量化SOM中使用的属性的权重。为了证明PCNP-SOM的适用性,给出了一个计算机产品推荐的例子。
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