【摘要】：為研究眼動(dòng)行為數(shù)據(jù)挖掘在提取網(wǎng)上購(gòu)物決策因子中的應(yīng)用,首先通過(guò)客戶體驗(yàn)管理(Customer Experience Management,CEM)對(duì)客戶網(wǎng)上購(gòu)物決策因子進(jìn)行初步分析和過(guò)濾;然后根據(jù)大量客戶網(wǎng)上購(gòu)物時(shí)的人機(jī)交互行為數(shù)據(jù),應(yīng)用馬爾科夫鏈算法預(yù)測(cè)其相關(guān)行為,并結(jié)合行為分析進(jìn)一步得到其重要影響因子;最后通過(guò)眼動(dòng)行為數(shù)據(jù)挖掘,確認(rèn)影響網(wǎng)上購(gòu)物的主決策因子,并獲取各主決策因子的權(quán)重.實(shí)驗(yàn)證明由眼動(dòng)分析獲取的網(wǎng)上購(gòu)物主決策因子及其權(quán)重更加有效.
[Abstract]:In order to study the application of eye movement behavior data mining in the extraction of online shopping decision factors, first, the customer experience management(CEM)is used to analyze and filter the decision-making factors of online shopping. Then, based on the data of man-machine interaction behavior of a large number of customers online shopping, the Markov chain algorithm is applied to predict their related behaviors, and the important influencing factors are further obtained by combining the behavior analysis. Finally錛，

本文編號(hào)：2476266