Deepening digital user understanding through large language model analysis of clickstream-based segments

This publication has 26 references indexed in Scilit:

• Building explainable artificial intelligence for reinforcement learning based debt collection recommender system using large language models
  Engineering Applications of Artificial Intelligence, 2025
• An explainable framework for assisting the detection of AI-generated textual content
  Decision Support Systems, 2025
• Harnessing generative AI for personalized E-commerce product descriptions: A framework and practical insights
  Computer Standards & Interfaces, 2025
• Focus on user micro multi-behavioral states: Time-sensitive User Behavior Conversion Prediction and Multi-view Reinforcement Learning Based Recommendation Approach
  Information Processing & Management, 2024
• A multi-step regularity assessment and joint prediction system for ordering time series based on entropy and deep learning
  Autonomous Intelligent Systems, 2024
• An experimental study on re-ranking web shop search results using semantic segmentation of user profiles
  Electronic Commerce Research and Applications, 2023
• RFM model customer segmentation based on hierarchical approach using FCA
  Expert Systems with Applications, 2023
• A review on customer segmentation methods for personalized customer targeting in e-commerce use cases
  Information Systems and e-Business Management, 2023
• Predicting online shopping behaviour from clickstream data using deep learning
  Expert Systems with Applications, 2020
• Customer segmentation in e-commerce: Applications to the cashback business model
  Journal of Business Research, 2018