Special Issue in AI and Web Data Analytics
In Transactions on Large-Scale Data and Knowledge-Centered Systems
https://www.irit.fr/tldks/

Guest Editors:
Belkacem Chikhaoui, TELUQ University, Canada; belkacem.chikhaoui@teluq.ca;
Zakaria Maamar, University of Doha for Science and Technology, Qatar, Zakaria.maamar@udst.edu.qa;

Description
Artificial Intelligence (AI) and its derivatives, particularly Large Language Models (LLMs), are transforming Web data analytics by enabling deep semantic understanding, information extraction, and insight generation from large-scale online data. AI-driven models play a crucial role in analyzing user interactions across Web applications, social media, and other platforms, helping researchers and practitioners uncover user intent, personalize experiences, and automate decision-making.

By leveraging advanced learning algorithms, NLP techniques, and generative AI, LLMs enhance information retrieval, summarization, semantic search, and knowledge extraction across heterogeneous and multilingual sources. Additionally, AI-driven analytics supports personalized search, recommendation systems, ethical AI deployment, and responsible data management. However, challenges such as misinformation, privacy concerns, and the scalability of AI-driven analytics remain critical areas of research.

This special issue seeks to provide a platform for researchers to showcase the latest developments, challenges, and opportunities in the field of AI and Web Data Analytics across diverse domains, fostering interdisciplinary innovation.

We invite authors to submit their research work that showcases theoretical advancements, practical applications, and industrial experiences at the intersection of AI, LLMs, Web analytics, and Web data mining. Topics of interest include, but are not limited to:
Web data representation, mining, and discovery
Deep learning and LLMs for Web data analytics
Mining and learning in Web data with missing information and noise
Explainable AI in Web data analytics
Responsible AI for Web technologies, standards, platforms, and applications
AI and LLM deployment for large-scale Web analytics
Social network data mining and analysis
Impact of misinformation and disinformation on Web data analytics
Privacy-enhancing technologies for Web data analytics
Efficiency and scalability of Web search engines
Multilingual and cross-lingual Web search using LLMs
Natural language understanding for Web search and question answering
Large language models for search and content generation
Semantic Web, semantic models, and knowledge graphs
LLMs for knowledge graph construction and reasoning
Influence propagation, information diffusion, and predictive modeling in networks
AI for personalized search and recommendations
Sentiment analysis, opinion mining, and user behavior modeling

Important Dates
Submissions deadline: April 30, 2025
First-round review decisions: June 30, 2025
Deadline for revision submissions: August 30, 2025
Notification of final decisions: September 30, 2025
Tentative publication: November 2025

Submission Information
Submissions must be prepared according to the TLDKS submission guidelines (https://www.irit.fr/tldks/submission/) and must be submitted online (https://equinocs.springernature.com/service/tldks-si-aiwda).

For questions and further information, please contact Prof. Belkacem Chikhaoui belkacem.chikhaoui@teluq.ca).