UNVEILING THE POWER OF USER-GENERATED CONTENT: A NOVEL APPROACH TO RANKING IN PRODUCT SEARCH ENGINES

Authors

Mei Ling Chen School of Management, Wuhan University of Technology, Wuhan, China
Xiang Wei Zhang School of Management, Wuhan University of Technology, Wuhan, China
Li Hua Wang School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China

DOI:

Keywords:

Web Growth, Search Engines, Product Search, Recommender Systems, Decision Accuracy

Abstract

The past two decades have witnessed an unprecedented surge in the growth of the internet, establishing it as a paramount source of information. Concurrently, search engines have evolved into the predominant means for information retrieval and access, emerging as pivotal channels for product promotion and sales (Ghose, Ipeirotis, and Li, 2013). Within this digital landscape, product search and recommender systems, collectively known as online systems, have emerged to aid users in navigating extensive electronic catalogs. These systems are designed with the primary objective of reducing consumers' time investment and purchase risk while enhancing decision-making precision (Pu, Chen, and Kumar, 2008).

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Published

2024-11-08

Issue

Vol. 12 No. 3 (2023): July-September

Section

Articles