PriceCop – Price Monitor and Prediction Using Linear Regression and LSVM-ABC Methods for E-commerce Platform

Abstract

In early 2020, the world was shocked by the outbreak of COVID-19. World Health Organization (WHO) urged people to stay indoors to avoid the risk of infection. Thus, more people started to shop online, significantly increasing the number of e-commerce users. After some time, users noticed that a few irresponsible online retailers misled customers by hiking product prices before and during the sale, then applying huge discounts. Unfortunately, the "discounted" prices were found to be similar or only slightly lower than standard pricing. This problem occurs because users were unable to monitor product pricing due to time restrictions. This study proposes a Web application named PriceCop to help customers' monitor product pricing. PriceCop is a significant application because it offers price prediction features to help users analyse product pricing within the next day; thus, it can help users to plan before making purchases. The price prediction model is developed by using Linear Regression (LR) technique. LR is commonly used to determine outcomes and used as predictors. Least Squares Support Vector Machine (LSSVM) and Artificial Bee Colony (ABC) are used as a comparison to evaluate the accuracy of the LR technique. LSSVM-ABC was initially proposed for stock market price predictions. The results show the accuracy of pricing prediction using LSSVM-ABC is 84%, while it is 62% when LR is employed. ABC is integrated into SVM to optimize the solution and is responsible for the best solution in every iteration. Even though LSSVM-ABC predicts product pricing more accurately than LR, this technique is best trained using at least a year's worth of product prices, and the data is limited for this purpose. In the future, the dataset can be collected daily and trained for accuracy.

Метод Оцінки Коефіцієнтів При Лінійних Членах Багатовимірної Поліноміальної Регресії, Заданої Надлишковим Описом

“…В багатьох інформаційних експертних системах чи в інформаційних системах класифікації використовуються багатовимірні лінійні чи нелінійні регресії, коефіцієнти яких при змінних знаходяться методом найменших квадратів [1][2][3][4][5][6][7][8]. В роботах [9][10][11] була сформульована наступна проблема.…”

Precise Marketing Strategy Optimization of E‐Commerce Platform Based on KNN Clustering

“…e experimental results indicated that supplier's profit can be affected by many aspects and show different effects. Shahrel et al [21] designed a Web application called Price Cop to help customers monitor product pricing, which helps users plan before they buy. A price forecasting model is established by using linear regression technique.…”

Activities of Illegal Weapons Criminal Component of Hybrid Threats

“…The purpose of the paper, based on factor analysis [8], is to identify homogeneous groups of hybrid threats in the civil security sector, analyze the risk level of hybrid threats' spreading of related to crime; on the basis of correlation analysis [9] to determine the factors that shape the capabilities or vulnerabilities [10] to reduce the risk of illegal armed groups. Based on the linear regression [11] model, to assess the risk of the spread of the hybrid threat "activities of illegal armed groups", to identify priority factors of reduce this risk and to build an appropriate model and forecast.…”