A Product Recommendation System for e-Shopping

被引：0

作者：

Imam, Muhammad Yasir ^{[1
]}

Usmani, Zain-ul-Abideen ^{[2
]}

Khan, Arsalan ^{[1
]}

Usmani, Osama ^{[3
]}

机构：

[1] Alhamd Islamic Univ, Dept Comp Sci & IT, Islamabad, Pakistan

[2] South Dakota State Univ, Elect Engn & Comp Sci, Brookings, SD 57007 USA

[3] Natl Univ Sci & Technol, Dept Informat Secur, Islamabad, Pakistan

来源：

2021 IEEE LATIN AMERICAN CONFERENCE ON COMPUTATIONAL INTELLIGENCE (LA-CCI) | 2021年

关键词：

recommendation system; machine learning; scrapping; web-based; decision maker;

D O I：

10.1109/LA-CCI48322.2021.9769830

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the increase in number of ecommerce websites, it is difficult for a user to find a reasonable product he/she wants. In addition, users have no way to find the best product for him rather than searching product on different website and looking for the best product suitable to him. Product recommendation system is a web-based system that solves the problem of users by helping them to decide which product suits them according to the features and price they require. Our system is independent of the structure of websites as it uses set of rules and matches the regular expressions of the specifications with the text of the website. This system is visualizing results graphically for the ease of user decision. This product recommendation system provides results realistically.

引用

页数：7

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