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An intelligent simulation model of online consumer behavior

机译:在线消费者行为的智能仿真模型

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This paper describes the design of an Intelligent Simulation Model of Online Consumer Behavior (ISMOCB) that incorporates a knowledge base using some form of the Artificial Intelligence methods such as Naïve Bayes Classifier and Artificial Neural Networks. This study investigates modeling online consumer behavior by using demographic characteristics such as age, gender, marital status, educational status, monthly income and number of people in the family. This will provide producing more synthetic data and creating an “Artificial Database” which includes the demographics of online consumers and their purchase transactions. The model is built for online shopping based on empirical data gathered in Turkey via an online survey. Two different inference systems are used for which product group is chosen by whom has which demographic characteristics. The quality of the data, gathered exclusively for this project, allows a fine validation of the simulation results.
机译:本文介绍了一种在线消费者行为智能仿真模型(ISMOCB)的设计,该模型结合了使用某种形式的人工智能方法(如朴素贝叶斯分类器和人工神经网络)的知识库。这项研究使用年龄,性别,婚姻状况,教育状况,月收入和家庭人数等人口统计特征,研究了在线消费者行为的建模。这将提供更多的综合数据,并创建一个“人工数据库”,其中包括在线消费者的人口统计及其购买交易。该模型是根据土耳其通过在线调查收集的经验数据构建的,用于在线购物。使用两种不同的推理系统为哪个产品组选择谁具有哪个人口统计特征。专为该项目收集的数据质量允许对仿真结果进行精细验证。

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