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Optimal design of link structure for e-supermarket website

机译:电子超市网站链接结构的优化设计

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The objective of this research is to optimize the link structure of webpages for an e-supermarket. Customers are looking for greater convenience in shopping when they visit the website of an e-supermarket, while e-supermarket managers prefer webpages that contain information about profitable products to be visited more frequently. In order to balance the interests of both parties and to aid the webmaster in updating the website regularly, we present a mathematical model with the objective of minimizing the overall weighted distances between webpages. An updating algorithm is used to determine the distance between pages. It is proved to be more efficient under certain special circumstances. We propose the statistical Hopfield neural-network and the strategic oscillation-based tabu-search algorithms as solving methods. The former is appropriate for optimizing small-scale problems. The latter is good at solving large-scale problems approximately. The preliminary validity of the model and the performance of the algorithms is demonstrated by experiments on a small website and several large websites, using randomly generated data. The destination pages that customers and website managers preferred are proved to be more accessible after optimization.
机译:这项研究的目的是为电子超市优化网页的链接结构。客户在访问电子超市的网站时正在寻求更大的购物便利,而电子超市经理则更喜欢包含有关获利产品信息的网页,以便更频繁地访问它们。为了平衡双方的利益并帮助网站管理员定期更新网站,我们提出了一个数学模型,目的是使网页之间的总加权距离最小。更新算法用于确定页面之间的距离。在某些特殊情况下,它被证明是更有效的。我们提出了统计Hopfield神经网络和基于策略振荡的禁忌搜索算法作为求解方法。前者适用于优化小规模问题。后者擅长于近似解决大规模问题。通过在一个小型网站和几个大型网站上使用随机生成的数据进行实验,证明了该模型的初步有效性和算法的性能。经过优化,事实证明,客户和网站管理员首选的目标页面更易于访问。

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