【摘要】：為研究眼動行為數(shù)據(jù)挖掘在提取網(wǎng)上購物決策因子中的應(yīng)用,首先通過客戶體驗管理(Customer Experience Management,CEM)對客戶網(wǎng)上購物決策因子進行初步分析和過濾;然后根據(jù)大量客戶網(wǎng)上購物時的人機交互行為數(shù)據(jù),應(yīng)用馬爾科夫鏈算法預(yù)測其相關(guān)行為,并結(jié)合行為分析進一步得到其重要影響因子;最后通過眼動行為數(shù)據(jù)挖掘,確認影響網(wǎng)上購物的主決策因子,并獲取各主決策因子的權(quán)重.實驗證明由眼動分析獲取的網(wǎng)上購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：2476266