6 citations
6 papers
Predicting California Bearing Ratio with Ensemble and Neural Network Models: A Case Study from Turkiye
Abdullah Hulusi Kökçam, Uğur Dağdeviren, Talas Fikret Kurnaz +2
The California Bearing Ratio (CBR) is a key geotechnical indicator used to assess the load-bearing capacity of subgrade soils, especially in transportation infrastructure and found…
Soil Compaction Parameters Prediction Based on Automated Machine Learning Approach
Caner Erden, Alparslan Serhat Demir, Abdullah Hulusi Kokcam +2
Soil compaction is critical in construction engineering to ensure the stability of structures like road embankments and earth dams. Traditional methods for determining optimum mois…
Augmented Web Usage Mining and User Experience Optimization with CAWAL's Enriched Analytics Data
Özkan Canay, {Ü}mit Kocabıcak
Understanding user behavior on the web is increasingly critical for optimizing user experience (UX). This study introduces Augmented Web Usage Mining (AWUM), a methodology designed…
CAWAL: A novel unified analytics framework for enterprise web applications and multi-server environments
Özkan Canay, Ümit Kocabıçak
In web analytics, cloud-based solutions have limitations in data ownership and privacy, whereas client-side user tracking tools face challenges such as data accuracy and a lack of…
Predictive modeling and anomaly detection in large-scale web portals through the CAWAL framework
Ozkan Canay, Umit Kocabicak
This study presents an approach that uses session and page view data collected through the CAWAL framework, enriched through specialized processes, for advanced predictive modeling…
An innovative data collection method to eliminate the preprocessing phase in web usage mining
Ozkan Canay, Umit Kocabicak
The underlying data source for web usage mining (WUM) is commonly thought to be server logs. However, access log files ensure quite limited data about the clients. Identifying sess…