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http://hdl.handle.net/1942/25507
Title: | Development of Customs Prediction Model for Online Ordering | Authors: | Sharawi, Lina I. QABBAAH, Hamzah SAMMOUR, George VANHOOF, Koen |
Issue Date: | 2018 | Publisher: | IEEE | Source: | Awajan, Arafat; Shaout, Adnan (Ed.). Proceedings: 2017 International Conference on New Trends in Computing Sciences (ICTCS), IEEE,p. 94-97 | Abstract: | As a result of the rapid increase of online shopping, and the movement of products in and out among various countries, governments made it mandatory to pay a certain fee referred to as customs to maintain each country’s economy, based on some rules i.e. weight and price. This paper proposes a model to anticipate and inform the customer if his order is going to be subject to customs or not based on some predefined rules. The model is built using a software called SPSS and data mining techniques such as; Decision Tree (DT) and logistic regression. A comparison between the two data mining techniques is made showing that the DT results were better than the logistic regression in terms of accuracy, precision, recall and f-score. | Notes: | Sharawi, LI (reprint author), PSUT, Software Engn Dept, Amman, Jordan. lin20148050@std.psut.edu.jo; Hamzah.qabbaah@uhasselt.be; George.sammour@psut.edu.jo; koen.vanhoof@uhasselt.be | Keywords: | data mining; customs; decision tree; logistic regression; classification measures | Document URI: | http://hdl.handle.net/1942/25507 | ISBN: | 9781538605271 | DOI: | 10.1109/ICTCS.2017.33 | ISI #: | 000425843800017 | Rights: | © 2017 IEEE | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2019 |
Appears in Collections: | Research publications |
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