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Designing a Model for Improving Banking Recommender Systems Based on Predicting Customers’ Interests: Application of Data Mining Techniques | ||
| Journal of Information Technology Management | ||
| مقاله 70، دوره 8، شماره 2، مهر 2016، صفحه 393-314 اصل مقاله (859.39 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jitm.2016.57230 | ||
| نویسندگان | ||
| Maryam sadat Motaharinejad1؛ Mohammad Mahdi Zolfagharzadeh* 2؛ Ehsan Khadangi3؛ Ali Asghar Sadabadi4 | ||
| 1MSc in Information Technology Management, Islamic Azad University E-campus, Tehran, Iran | ||
| 2Assistant Prof., Faculty of New Sciences and Technologies, University of Tehran, Iran | ||
| 3Ph.D. Student in Computer Engineering, Amirkabir University of Technology, Tehran, Iran | ||
| 4PhD student in science and technology policy, Faculty of New Sciences and Technologies, University of Tehran, Tehran | ||
| چکیده | ||
| Nowadays, banks require new devices such as recommender systems to attract and preserve customers. Unlike most recommender systems in which the given recommendation is based on similarities between the preferences of users, this research has employed the classification techniques where customer’s past interests is considered as the most important feature to provide proper banking services for them. In this research, four classifiers including MLP, SVM, KNN, and Naïve Bayes have been used. Firstly, the data set which was related to the services used by different bank customers was pre-processed and four different classification methods were trained by using it. Then, their validations were assessed by the 10-fold cross validation and the best method was selected. Lastly, the final recommender system which was a combination of four classification methods including Naïve Bayes with performance P=%85.4, 5-nn with P=%83.3, MLP with P=%81.4, and MLP with P=%92.6 respectively proposed for recommendation of four banking services including the internet, mobile, internet transfer and paying on the phone is. | ||
| کلیدواژهها | ||
| Classification؛ Data Mining؛ E-Banking؛ Recommender System | ||
| مراجع | ||
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