Enhancing Ad Relevance using Data Mining and Ad Profiling

Abstract

Digital advertising is a dynamic landscape, and despite this fact, ensuring ad relevance to the user remains a challenge. The online web industry relies on the keywords the advertisers assign to find the target audience for the ads; however, while efficient enough, this technique has limitations, particularly concerning ad relevance to the content and the user targeted. This project deals with the problem of keyword mismatching, exploring the impact of broad match keywords, negative keywords and keyword synonyms on the overall relevance of ads on the internet.