About the workshop

Artificial Intelligence (AI) and its derivatives are revolutionizing the landscape of Web data analytics. AI models are extensively used to collect, process, analyze, and report data on how people interact with Web applications, social media, and other online platforms. They can help understand a Web site’s audience in terms of preferences, behaviors, and reactions. AI can automate, improve, and personalize Web analytics, through learning and natural language processing algorithms. It can also help generate insights, recommendations, and actions based on Web data analytics. The 2nd International Workshop on AI and Web Data Analytics (AIWDA 2025) to be held in conjunction with The International Web Information Systems Engineering Conference (WISE 2025) is an excellent international forum to share knowledge and results in theory, techniques, and applications of recent developments of blending AI with Web Data Analytics.

Call for papers

The workshop solicits contributions in major fields of AI, Web analytics, Data analytics, and social networks from theoretical and practical perspectives.

Topics of Interest

Authors are invited to contribute to the workshop by submitting papers that showcase research findings, innovative projects, surveys, work in progress, and industrial experiences that highlight significant advances in the following topics but not limited to:

  • Web data representation, mining, and discovery
  • Deep learning for Web data analytics
  • Mining and learning in Web data with missing information and noise
  • Explainable AI in Web data analytics
  • Responsible AI of Web technologies, standards, platforms and applications
  • AI algorithmic deployment on the Web
  • Social network data mining
  • 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
  • Natural language understanding for Web search
  • Large language models for search
  • Semantic Web, semantic models, knowledge graphs
  • LLMs for knowledge graphs
  • Influence propagation, information diffusion, and the prediction on networks (link prediction, node or subgraph prediction)
  • AI for personalized search and recommendations
  • Sentiment analysis and opinion mining

Audience

The workshop will be of interest to AI and Web data analytics researchers and industrial practitioners who would like to tap into Web data analytics-related opportunities like best practices, lessons learned, challenges tackled, issues addressed, and success stories to ensure a successful blend of AI with Web data analytics. Web data analytics is a well-established discipline that is backed by many years of R&D and hence, could help AI become the technology of choice for the development of Web data analytics systems.

Timetable

As per the call for proposals, the workshop will adhere to the specified deadlines for submission and notification:

  • Submission Deadline: October 15, 2025
  • Author Notification: October 30, 2025
  • Final Manuscript Due: November 15, 2025

Submission Guideline

Papers should be submitted in PDF format. The results described must be unpublished and must not be under review elsewhere. Submissions must conform to Springer’s LNCS format and should not exceed 15 pages, including all text, figures, references, and appendices. Submissions not conforming to the LNCS format, exceeding 15 pages, or being obviously out of the scope of the conference, will be rejected without review. Information about the Springer LNCS format can be found at Springer. Three to five keywords characterizing the paper should be indicated at the end of the abstract.

All papers should be submitted via Easychair. Make sure to select Workshop 1: AI and Web Data Analytics @ WISE-2025.

Paper Review Process And Acceptance Standards

Each submission will be peer-reviewed by 2-3 PC members. Selection criteria include relevance, significance, impact, originality, and technical soundness. Preference will also be given to submissions covering emergent trends in shaping the blend of AI with Web data analytics.

Publications

Accepted papers will be presented at AIWDA’2025 Workshop and published as per WISE’s guidelines for workshop proceedings publication. Authors of high-quality papers and presentations will be invited to submit extended versions of their work to reputable journals.

Committees

Program Committee

  • Jean Marie Tchimula Kabamba, University of Sherbrooke, Canada
  • Richard Hotte, TELUQ University, Canada
  • Nizar Bougouila, Concordia University, Canada
  • Shengrui Wang, University of Sherbrooke, Canada
  • Sami Yangui, University of Toulouse, France
  • Mahdi Zargayouna, IFSTTAR, France
  • Marco Aiello, University of Stuttgart, Germany
  • Alex Aklson, IBM, Canada

Organizing Committee

General co-chairs

  • Belkacem Chikhaoui, TELUQ University, Montreal, Canada
  • Zakaria Maamar, University of Doha for Science and Technology, Doha, Qatar
  • Essaid Elbachari, Cadi Ayyad University, Marrakech, Morocco

Program co-chairs

  • Reda Bendraou, University of Doha for Science and Technology, Doha, Qatar
  • Ossama Djedidi, University of Doha for Science and Technology, Doha, Qatar

Publicity chair

  • Amine Mohamed Saleh Benouar, University of Doha for Science and Technology, Doha, Qatar

Workshop venue

The workshop will be held in Palm Plaza Hotel & Spa in Marrakech.

Palm Plaza Hotel & Spa
Avenue du 7ème Art
Agdal, 40000 Marrakech
Morocco

Localisation

Offered by

Founded in 1972 as part of the University of Quebec network, TÉLUQ University is the only French-speaking institution of university education in North America that is exclusively dedicated to distance education. As a pioneer and leader in this teaching mode, it offers more than 140 programs and 530 courses at the graduate and undergraduate level. Providing enhanced access to knowledge, TÉLUQ University allows around 20,000 people each year to combine their university studies with their personal and professional projects.