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首页> 外文期刊>WSEAS Transactions on Computers >Density-Based Clustering by P System with Active Membranes on Commodity Recommendation in E-commerce Websites
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Density-Based Clustering by P System with Active Membranes on Commodity Recommendation in E-commerce Websites

机译:电子商务网站中基于商品推荐的具有主动膜的P系统基于密度的聚类

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摘要

With the Popularity of shopping online in people's daily economic life, the commodity recommendation mechanism in e-commerce platform is presented to help customers quickly and accurately find the suitable product. Using the possibility of changing membrane structure, a variant of P system with active membranes is proposed to solve commodity recommendation problems. In this paper, the commodity recommendation problem is transformed into a density-based clustering problem firstly. Then it specifies the procedure of realizing this problem and a P system with a sequence of new rules is designed. The computation complexity of DBSCAN clustering algorithm in this system is O(n log n), while the original DBSCAN clustering algorithm is O(n~2) without spatial query. This new model of P system can reduce the computation complexity of clustering process and improve the efficiency to solve the problems of commodity recommendation. Through example verification, this new model of P system is proved to be feasible and effective to achieve this practical issue.
机译:随着人们日常经济生活中网络购物的普及,提出了电子商务平台中的商品推荐机制,以帮助客户快速,准确地找到合适的产品。利用改变膜结构的可能性,提出了具有活性膜的P系统的变体,以解决商品推荐问题。本文首先将商品推荐问题转化为基于密度的聚类问题。然后,它指定了实现此问题的过程,并设计了具有一系列新规则的P系统。该系统中DBSCAN聚类算法的计算复杂度为O(n log n),而原始DBSCAN聚类算法为O(n〜2),无空间查询。这种新的P系统模型可以降低聚类过程的计算复杂度,提高解决商品推荐问题的效率。通过实例验证,该新的P系统模型被证明是可行且有效的解决这一实际问题的方法。

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