• IEEE Computational Intelligence Society Task Force:
    Fuzzy Systems for Web Intelligence

    to promote research, development and usage of fuzzy-based methodologies and techniques for exploring the web and making it more intelligent and human-like

Statement and goals

Web intelligence is the area of scientific research and development that explores the roles and makes use of artificial intelligence and information technology methodologies for enabling the design and implementation of new products, services and frameworks that are empowered by the World Wide Web. In particular, Web intelligence achieves this goal through a combination of digital analytics, which examines how website visitors view and interact with a site’s pages and features, and business intelligence, which allows a corporation’s management to use data on customer purchasing patterns, demographics, and demand trends to make effective strategic decisions. As an example, search engines are one of the Internet applications that better benefit from this innovative method.

Thanks to the aforementioned combination of technologies, Web Intelligence enables the implementation of enhanced systems aimed at improving users' experience in using and manipulating web resources, and companies' activities in deploying profiled and personalised contents and services. However, the imprecise and vague nature of World Wide Web, due to the large amount of information online and the different types of interaction that users and companies can have with this information, requires a new vision of web intelligence in which the treatment of uncertainty is a key factor.

Indeed, recent literature review suggests that more and more successful developments in Web Intelligence are being integrated with fuzzy sets to enhance smart functionality such as web search systems by fuzzy matching, Internet shopping systems using fuzzy multi-agents, product recommender systems supported by fuzzy measure algorithms, e-logistics systems using fuzzy optimisation models; online customer segments using fuzzy data mining, fuzzy case-based reasoning in e-learning systems, and particularly online decision support systems supported by fuzzy set techniques. In light of the these observations, this special session is intended to form an international forum presenting innovative developments of fuzzy set applications in Web-based support systems.

The ultimate objective is to bring well-focused high quality research results in Fuzzy Web Intelligence systems with intent to identify the most promising avenues, report the main results and promote the visibility and relevance of fuzzy sets.

Research Areas

  • Fuzziness in Web-based group support systems
  • Fuzziness in Web-based decision support systems
  • Fuzziness in Web-based personalised recommender systems
  • Fuzziness in Web-based knowledge management systems
  • Fuzziness in Web-based customer relationship management
  • Fuzziness in Web-based tutoring systems
  • Fuzzy Technology in e-Business intelligence
  • Fuzzy Technology for search engine design
  • Fuzzy Technology in e-Commerce intelligence
  • Fuzzy Technology in e-Government intelligence
  • Fuzzy Technology in e-Learning intelligence
  • Fuzzy Technology in e-Health intelligence
  • Fuzzy Ontologies
  • Fuzzy Sets and Semantic Web Applications
  • Web-based technologies for Fuzzy Reasoning
  • Fuzzy Markup Language and Applications


Fuzziness and New Frontiers of AI Research

Fuzzy sets and systems as an important technique of artificial intelligence (AI) provide important and non-trivial approaches, techniques and methods suitable for dealing with a number of issues and challenges directly or indirectly related to better understanding of data and systems used for its analysis and processing. It is of special importance in the area of increasing complexity of algorithms and techniques leading to models with low interpretability as well as low man-machine interaction.

It is anticipated that the integration of fuzziness and soft computing technologies with new AI techniques results in developing user-friendly systems with explainable reaction and human supervision.

The aim of this session is to focus on the cross-fertilization of various techniques elaborated under the umbrellas of fuzzy sets and systems and variety of other AI research topics with emphasis on machine and deep learning, reinforcement learning, as well as internet of things and human-centric systems.

The special session will focus on the current research trends in the area of theory and practical aspects of application of fuzzy set and system methods suitable for addressing issues specific to the new AI technologies.

Special Session Topics

  • Explainable AI:
  • identifying what-if scenarios
  • understanding models’ behavior
  • look inside of models

  • Internet of Things:
  • information fusion
  • sensor data integration
  • Deep learning:
  • understanding classification/identification tasks
  • improving quality of fuzzy systems

  • Reinforcement learning:
  • fuzzy dynamic programming
  • agent interaction

  • Human-centric systems
  • semantic-based processing of data
  • linguistically rich computation

Important Dates

  • Paper Submission: January 15, 2020
  • Notification: March 15, 2020
  • Final Paper Submission: April 15, 2020


  • Irina Perfilieva, University of Ostrava, Czech Republic
  • Jie Lu, University of Technology Sydney, Australia
  • Marek Z. Reformat, University of Alberta, Canada


About Us

We focus on the current research trends in the area of theory and practical aspects of intelligent systems equipped with fuzzy and other soft computing methods suitable for solving issues specific to web utilization, as well as to representation and processing of information and knowledge with special emphasis on fuzzy ontologies, and their applications in various domains.

Giovanni Acampora
University of Naples Federico II, Italy
Valerie Cross
Miami University, OH, USA
Chang-Shing Lee
National University of Tainan, Taiwan
Vincenzo Loia
Università degli Studi di Salerno, Italy
Trevor Martin
University of Bristol, UK
Gabriela Pasi
University of Milano Bicocca, Italy
Marek Reformat
University of Alberta, Canada
Sabrina Senatore
Università degli Studi di Salerno, Italy
Dominik Slezak
University of Warsaw, Poland
Susana Vieira
University of Lisbon, Portugal
Ronald R. Yager
Iona College, NY, USA
Yiyu Yao
University of Regina, Canada

Contact Us


If you have any questions or would like to join the group, please do not hesitate to contact us.
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