Recommendation Systems For E-commerce Systems An Overview

Abstract

Due to the huge expand in global markets and financial transactions, the importance of E-commerce has grown significantly, so to achieve fully functioning, scalable, reliable, efficient, secure, and user-friendly E-commerce system, Adequate system analysis and design procedures are essential. On the other hand The internet vast growing has totally altered the way most companies work. The Internet has created a means for e-Commerce the internet has created a way to provide a unique avenue for companies and customers to sell and buy goods and services. When creating an e-commerce website, there are several goals that must be taken into account, one of them is how to Increase the site’s efficiency to ensure customer turnout and thus achieve the required material profits. There are several methods that are followed to increase the efficiency of the site. One of these methods is the recommender system. This paper produces a study overview of the value of recommended systems and thoroughly analyzed Collaborative Recommender System (CF) techniques with its techniques., which presents proposals to customers according to their interests, making it easier for the customer to search and thus choose the goods that suit him.

E-commerce and consumer behavior: A review of AI-powered personalization and market trends

“…AI-powered personalization plays a pivotal role in shaping consumer decision-making by providing tailored and relevant experiences. Through sophisticated algorithms, e-commerce platforms analyze vast datasets, including user preferences, purchase history, and browsing behavior, to deliver personalized product recommendations and content (Hussien et al, 2021). This level of customization not only simplifies the decision-making process for consumers but also enhances their overall satisfaction.…”

Recommender systems: A systematic literature review, synthesis and framework for future capabilities

“…Platforms such as Amazon.com, Myntra, Flipkart, etc., offer an extensive array of product categories, thereby presenting users and consumers with the formidable challenges of navigating through abundant choices. This dilemma directly impacts consumer purchasing behavior, thus exerting a direct influence on sales metrics (Abdul Hussien et al, 2021). In this context, recommender systems play a pivotal role in optimizing the performance of ecommerce platforms.…”

Hybrid-based Recommender System for Online Shopping: A Review

“…Furthermore, the user-based CF technique is transformed into an item-based CF technique, which produces predictions based on the similarities of items [20]. In the item-based CF technique, the idea is to recommend products to customers that are similar to products the customers have previously rated.…”