Fuzzy Logic Approach For Visual Analysis Of Websites With K-means Clustering-based Color Extraction

TL;DR

This paper presents a fuzzy logic-based method utilizing K-means clustering to analyze and quantify website aesthetic appeal through color harmony and font popularity, aiming to enhance user experience.

Contribution

It introduces a novel fuzzy logic approach for assessing website aesthetics based on color and font features, using a new dataset of real-world website designs.

Findings

Color harmony correlates with user engagement.

Fuzzy logic effectively predicts aesthetic preferences.

Dominant color extraction improves aesthetic analysis.

Abstract

Websites form the foundation of the Internet, serving as platforms for disseminating information and accessing digital resources. They allow users to engage with a wide range of content and services, enhancing the Internet's utility for all. The aesthetics of a website play a crucial role in its overall effectiveness and can significantly impact user experience, engagement, and satisfaction. This paper examines the importance of website design aesthetics in enhancing user experience, given the increasing number of internet users worldwide. It emphasizes the significant impact of first impressions, often formed within 50 milliseconds, on users' perceptions of a website's appeal and usability. We introduce a novel method for measuring website aesthetics based on color harmony and font popularity, using fuzzy logic to predict aesthetic preferences. We collected our own dataset, consisting of nearly 200 popular and frequently used website designs, to ensure relevance and adaptability to the dynamic nature of web design trends. Dominant colors from website screenshots were extracted using k-means clustering. The findings aim to improve understanding of the relationship between aesthetics and usability in website design.