A study on prediction of user's tendency toward purchases in websites based on behavior models

• Published in: 2014 6th Conference on Information and Knowledge Technology (IKT) pp. 61 - 66
• Main Authors: Gohari Boroujerdi, Emad, Mehri, Soroush, Sadeghi Garmaroudi, Saeed, Pezeshki, Mohammad, Rashidi Mehrabadi, Farid, Malakouti, SeyyedSalim, Khadivi, Shahram
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2014
• Subjects: Classification; Data Mining; Electronic mail; Feature Selection; Knowledge Discovery; Logistics; Machine Learning; Purchase Intention; User Behavior
• DOI: 10.1109/IKT.2014.7030334

Nowadays customers would rather buy their needs online than visiting a retail store because of many reasons such as saving time. Therefore, in order to increase efficiency of online shopping websites, many companies have invested in researches toward prediction of users purchases and recommendation systems that may help and motivate a user to buy products that he may be interested in. However, most efforts in this area has been around classification and predictions based on users interests in specific types of products. In this paper, we have studied efficiency of numerous algorithms toward building a classification model to predict the probability of a complete purchase by users only based on their behavior models in the system and regardless of their interest. Therefore, we experimented accuracy of different algorithms and proposed a novel classification model that is able to predict whether a user will be interested in buying a certain set of products that are placed in the online shopping cart or not.