Abstract

This study introduces a model for supporting the consumer’s cell phone purchase decisions by determining the phone status and recommending an estimated price for the phone. According to economic reasons, many people may have to buy used products. As the price for used cell phones is usually estimated while trading between the seller and the buyer which do not guarantee the best and fair price, this situation has emerged the idea of this study. We consider the idea of the proposed model is novel as up to our knowledge, all proposed online systems do not guarantee a fair price, they only focus on providing a link between the buyer and the seller and provide the seller’s required price with no recommendation of whether this price is fair or not. The proposed model has a set of defined criteria for status estimation. The values for some of these criteria are detected by applying of digital image processing technique on the phone photos and then a classification model is applied to determine its category and its estimated price. The recommendation system has been built based on the proposed model. Moreover, a web application with a user friendly interface has been developed and a number of cases for Samsung cell phones have been conducted which proved the applicability of the model.

Keywords:

Classification algorithms, e-commerce, image processing , online shopping , supervised learning,

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Competing interests

The authors have no competing interests.

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