Web Search Personalization in E-Commerce Sites Using Fuzzy Logic System

Abstract

In recent times, web mining is a process to obtain knowledge from the documents across the web. The web personalization system usually overcome various difficulties that includes entity interest, their inclination and requirements, and offers personalized knowledge to the users. Considering such limitations we develop a web page recommendation system that works in accordance with conventional collaborative filtering process. In this paper, we model a Fuzzy C-means that predicts the behavior of user in an e-commerce platform. The prediction of user behavior using Fuzzy C-means enables the model to provide web page recommendations based on the demands in the times like pandemic. The categorization of potential items enables easier association of web page recommendation using Fuzzy C-means clustering. The simulation is conducted to validate the efficacy of the model with conventional web page recommendation systems.