Dynamic Generation of Website Content Based on User Segmentation Using Artificial Intelligence

N. Kojić, Mladen Petrović, Natalija Vugdelija
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引用次数: 0

Abstract

The aim of this work is the segmentation of website users on the basis of artificial intelligence with the aim of dynamically modifying the content of the website for users, in accordance with the objectives of Web 4.0, and in this way enabling quick and optimal display of content follow­ing their needs. User classification will be based on click events on catego­ries/subcategories and articles. Based on that information, using Konon­en’s neural network, the user will be classified into one of the n categories to which the neural network was initially trained. Based on the detected type of the user’s classification, the content of the site is dynamically changed to the user, and the categories and products for which the majority of users of that type of classification have expressed greater interest are initially dis­played and offered. The goal is to adapt the content of the site to the needs of the user and in this way the user can easily and quickly find the desired product.
基于用户细分的人工智能网站内容动态生成
这项工作的目的是在人工智能的基础上对网站用户进行细分,目的是根据Web 4.0的目标,为用户动态修改网站的内容,从而能够根据用户的需求快速、最佳地显示内容。用户分类将基于点击事件对类别/子类别和文章。基于这些信息,使用Konon-en的神经网络,用户将被分类到神经网络最初训练到的n个类别中的一个。根据检测到的用户分类类型,网站的内容被动态地更改给用户,并且最初显示和提供该类型分类的大多数用户表示更感兴趣的类别和产品。目标是使网站的内容适应用户的需求,这样用户就可以轻松快速地找到想要的产品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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