A Systematic Review of Web Usage Mining Techniques and Future Research Options
Brent Van Aartsen, Omar El-Gayar, Cherie Noteboom · Open PRAIRIE (South Dakota State University) · 2020
Web usage mining, “WUM”, is an application of data mining techniques on web log data in order to understand the who, what, why, and how of those using a website. Through this systematic review, we look at the research of WUM techniques from 2014 - 2019 in order to understand the current state of WUM research as well as answer our research questions. Our research questions are (RQ1) what data sources are used in web usage mining, (RQ2) what data analysis methods are used to extract the knowledge, (RQ3) what are the applications of Web usage mining, and (RQ4) what future research can be done in the web usage mining area? Using a PRISMA approach to narrow the initial 778 search results, we completed a full analysis of 68 unique articles from four databases: Web of Science, ProQuest, ScienceDirect, and IEEE Xplore. Our article searches focused on the keywords (i) “web usage mining”, (ii) “WUM”, and (iii) “web usage AND mining”. The completion of the article analysis revealed research into WUM is on the decline. The analysis also revealed Personalization and Recommender Systems are the two most heavily researched applications of WUM.