List of accepted sessions

S1: Computational Intelligence in Database and Information Retrieval Systems

ORGANIZERS

• Janusz Kacprzyk (Polish Academy of Sciences, Warsaw, Poland)
• Gabriella Pasi (Università degli Studi di Milano-Bicocca, Milan, Italy)
• Guy De Tré (Ghent University, Ghent, Belgium)
• Slawomir Zadrozny (Polish Academy of Sciences, Warsaw, Poland)
• Antoon Bronselaer (Ghent University, Ghent, Belgium)

The organization of this session is an initiative of the EUSFLAT Working Group on Soft Computing in Database Management and Information Retrieval.

SCOPE

Information management systems, in particular database management systems and information retrieval systems, have become crucial components in many businesses and organizations. Computational intelligence techniques can play an important role in extending the facilities and effectiveness of such systems, in order to make them better accessible and to cope with uncertainties and other forms of imperfections in data and information.

Big data volumes, faster processing requirements, heterogeneous data structures and higher demands with respect to data quality further strengthen the need for advanced techniques to efficiently handle data imperfections in database and information retrieval systems. This special session will be an exciting opportunity to exchange ideas and to discuss theoretical and experimental results in this research domain. Hopefully, it will contribute to identifying new promising directions of research and unsolved problems in this area.

We invite contributions that focus on the application of:

• fuzzy set theory
• fuzzy logic
• computational intelligence

within the following, non-exhaustive, list of fields of:

• relational database modelling and querying
• non-relational, notably NoSQL, database management paradigms
• distributed databases management, including blockchain technology
• textual information retrieval
• big data processing
• data warehouse systems
• data quality
• data integration
• geographical information systems
• multimedia information systems
• semantic data processing within database management and information retrieval systems

We encourage submissions of papers, which have not been published or submitted to any other conference, about theoretical advances in these core areas as well as papers which deal with some practical insights resulting from experiments or implementations.

S2: Fuzzy Systems in Business and Economics

ORGANIZERS

• José M. Merigó (University of Technology Sydney, Australia and University of Chile, Chile)
• Joan Carles Ferrer Comalat (University of Girona, Spain)
• Salvador Linares Mustaros (University of Girona, Spain)
• Rajkumar Verma (University of Chile, Chile)

This session is sponsored by the International Association for Fuzzy Systems in Management and Economics (SIGEF).

SCOPE

Business and economics are social sciences fundamental for our modern society. The development of new quantitative theories for a better understanding of these fields has grown a lot during the last years. Today, there are many new ideas in the literature that use fuzzy systems and other soft computing methods for dealing with a business or economic problem. This Special Session aims to present applications of fuzzy systems and soft computing in any area connected to business and economics including decision-making, finance, marketing, accounting, strategy and econometrics.

Indicative Topics/Areas:

• Fuzzy business,
• fuzzy economics,
• fuzzy management,
• fuzzy strategy,
• fuzzy econometrics,
• fuzzy insurance,
• fuzzy finance,
• fuzzy marketing,
• fuzzy accounting,
• decision making,
• expert systems,
• other soft computing applications in business and economics.

All submitted papers of Special Sessions have to undergo the same review process. The technical reviewers for each Special Session paper will be members of the EUSFLAT 2019 Program Committee and qualified peer-reviewers to be nominated by the Special Session organizers.

S3: Fuzzy methods in Data Mining and Knowledge Discovery

ORGANIZERS

• M. Dolores Ruiz (University of Granada, Spain)
• Juan Gómez-Romero (University of Granada, Spain)
• Maria J. Martin-Bautista (University of Granada, Spain)
• Daniel Sánchez (University of Granada, Spain)

SCOPE

The objective of the special session is to provide a forum for the discussion of recent advances in the development and application of Data Mining and Knowledge Discovery technologies to diverse problems, focusing on those involving fuzzy methods, and to offer an opportunity for researchers to identify new and promising research directions.

Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making in the current ultra-competitive markets; (b) the large volume of data managed by organizations makes it impossible to carry out an analysis process manually.
Nowadays, the volume of information digitally stored has considerably increased not only in database format but also in text format which is available in open source bases such as the Web, including log files registering the use of the information or social media content. This has contributed to increase the interest on Text and Web Mining techniques. In one hand, these techniques aim to automatize the analysis process by introducing a variety of intelligent techniques to learn, optimize and represent uncertain and imprecise knowledge. On the other hand, these tools offer the possibility to analyze massive data offering more efficient algorithms and a suitable selection of obtained results in terms of their novelty, usefulness and interpretability

Topics of interest include, but are not limited to, the following topics:

• Imprecision, uncertainty and vagueness in data mining
• Data, text and web mining
• Stream data mining
• Temporal data series
• Big data mining
• Data mining for security
• Data pre- and post- processing in data mining
• Parallel and distributed data mining algorithms
• Information summarization and visualization
• Human-machine interaction for data access
• Semantic models to represent input data and extracted knowledge in a Data Mining process
• Applications of Data Mining techniques: health, tourism, biological process, customer profiles, anomaly detection, emergency management, situation recognition, etc.

S4: Representing and Managing Uncertainty: different scenarios, different tools

ORGANIZERS

• Davide Ciucci (University of Milano-Bicocca, Italy)
• Chris Cornelis (Ghent University, Spain)
• Jesús Medina (University of Cádiz, Spain)
• Dominik Slezak (University of Warsaw, Poland)

SCOPE

The notion of vagueness has been extensively analysed in the last decades by philosophers, logicians and computer scientists. Here we are interested in the vagueness originated by different characteristics and flaws in information: incompleteness, imprecision, graduality, granularity, contradiction between agents, etc. For each of these aspects one (or more) specific tool has been introduced in literature: fuzzy sets, rough sets, formal concept analysis, possibility theory, Dempster-Shafer theory, interval analysis, compound objects comparators, etc. Further, when more than one form of vagueness are present at the same time, it seems natural to fuse such tools, as in the fuzzy rough set case. The special session is devoted to collect all contributions that deal with scenarios leading to a form of vagueness and tools to represent and manage it. In particular, all critical discussions, comparisons among two or more forms of vagueness and/or comparisons and fusion of two or more tools are welcome.

The not exhaustive list of topics includes:

• rough sets (classical, probabilistic, game-theoretic, etc.)
• fuzzy rough sets
• interval-valued fuzzy sets
• formal concept analysis
• possibility theory
• Dempster-Shafer theory
• supervaluations
• near sets
• interval analysis
• grey sets
• non-classical logics (many valued, paraconsistent, epistemic, etc.)
• similarity-based reasoning

S5: Formal Concept Analysis and Applications

ORGANIZERS

• Radim Bělohlávek (Palacký University, Czech Republic)
• Inma P. Cabrera (Universidad de Málaga, Spain)
• Pablo Cordero (Universidad de Málaga, Spain)
• Jan Konečný (Palacký University, Czech Republic)

SCOPE

Formal Concept Analysis (FCA) currently represents a solid choice in data mining and knowledge discovery. Much of the recent interest in this area is due to its unique and general framework that allows developing from beginning to the end all the stages involved in the path from information to knowledge and, moreover, reason automatically about it. Its solid theoretical foundations make it possible to tackle problems such as the discovery of knowledge, its representation and automated reasoning, in a unified framework. Directly related to FCA are areas such as logic, algebra and lattice theory, data mining, information retrieval, knowledge management, data and knowledge engineering, to name just a few.
Interest in FCA led to a wide range of real applications in various domains such as biomedicine, bioinformatics, economics, education, tourism, social networks, etc.
Over the past few years, research on expanding FCA theory to deal with imprecise, incomplete, and vague information has made significant progress, as documented by developments in FCA of data with fuzzy attributes, interactions of FCA with granular computation, possibility theory, FCA of triadic data, interval-valued data to name the most prominent directions.

Topics include but are not limited to:

• Theoretical foundations in FCA
• Algorithms for FCA
• Logic and fuzzy logic, and FCA
• Attribute implications, association rules and data dependencies
• Redundancy and dimensionality reduction
• Knowledge discovery and data analysis
• Conceptual Exploration
• Ontologies

S6: Theory and Applications of Intuitionistic Fuzzy Sets

ORGANIZERS

• Krassimir Atanassov (Bulgarian Academy of Sciences, Bulgaria)
• Sotir Sotirov (Prof. Asen Zlataro” University, Bulgaria)
• Janusz Kacprzyk (Polish Academy of Sciences, Poland)
• Oscar Castillo (Tijuana Institute Technology, Mexico)
• Panagiotis Chountas (Westminster University, United Kingdom)
• Alzbeta Michalikova (Matej Bel University, Slovakia)

SCOPE

Intuitionistic fuzzy sets (IFS), proposed in 1983 by Atanassov, are one of the most viable and extensively studied extensions of the concept of Zadeh’s fuzzy sets. They gained the attention of many researchers worldwide and are employed in many axes of application. The scope of this special session is to bring together the IFS research community and address a variety of theoretical, application and software aspects, such as research of the foundations of the IFS and intuitionistic fuzzy logics (IFL), existing and novel extensions of the IFS, IFL and studying their properties, application of the apparatus of IFS and IFL in various areas, development of IFL-based software and decision making tools, as well as other relevant IFS-related research.

Topics include but are not limited to:

• Operations, relations, operators over IFS and IFL
• Algebraic, topological, geometrical and other aspects of IFS
• Norms, metrics and distances over IFS and IFL
• Extensions of IFS and IFL
• Software for implementation and visualization of IFS and IFL
• Applications of IFS and IFL in big data, data mining, machine learning, image recognition
• Applications of IFS and IFL in nature inspired and metaheuristic algorithms, clustering, etc.
• Intercriteria analysis and other IFS-based decision making tools
• Medical and biological applications of IFS and IFL
• Business, management, industrial and other applications of IFS and IFL
• Other related topics

S7: Fuzzy graphs and discrete models

ORGANIZERS

• Laszlo T. Koczy (Budapest University of Technology and Szechenyi Istvan University, Hungary)

SCOPE

Manuscripts on topics related to fuzzy graphs and other discrete models, like fuzzy state machines, fuzzy cognitive maps, etc. may be submitted. Some examples for welcome topics:

• In traditional mathematics, many graph search problems are NP-hard, while various meta-heuristics often provide efficient polynomial algorithms delivering results with high accuracy in reasonably short time. Such approaches extended to fuzzy graph search problems are of interest.
• Fuzzy edge, and edge and node graphs in modeling various real life phenomena, such as reliable and limited capacity networks, multiple feature descriptors of data (fuzzy-fuzzy signatures), and others.
• Fuzzy state machines and cognitive maps describing the dynamic behavior of vague discrete systems

S8: Evolving and adaptive fuzzy models for data streams

ORGANIZERS

• Giovanna Castellano (University of Bari Aldo Moro, Italy)
• Stefano Rovetta (University of Genova, Italy)
• Zied Mnasri (University of Tunis El Manar, Tunisia)

SCOPE

Nowadays a wide range of real-world scenarios yield data streams, i.e. collections of data being generated continuously either over time or over space. E-commerce and banking transactions, weather forecasting recordings and sensor data, customer reports and network traffic records are common examples of data streams produced every day. Accordingly there is an urgent need of methods capable to handle and analyze streams of data that are usually vast in volume (or possibly infinite), high-dimensional and changing dynamically. Analysis of data streams requires models that are specifically designed to adapt continuously and automatically to smooth evolutions (drifts) and abrupt changes (shifts) in the data distribution. Evolving intelligent systems (EIS) is an emerging field that focuses on adaptive evolving models in soft computing. The main objective of this special session is to discuss the potential of fuzzy techniques to develop EIS for prediction and classification tasks in challenging scenarios involving data streams.

Topics: The special session is intended to collect novel ideas and share different experiences in the field of evolving fuzzy models for data streams. Submission of papers covering theoretical and application aspects of evolving fuzzy models are encouraged. Possible topics include (but are not limited to):

• Learning in non-stationary environments
• Online/incremental fuzzy clustering
• Fuzzy techniques for data stream mining
• Evolving Fuzzy Systems
• Evolving Rule-Based Classifiers
• Evolving Neuro-Fuzzy Systems
• Adaptive Evolving Fuzzy Systems
• Online Genetic and Evolutionary Algorithms
• Adaptive Pattern Recognition
• Incremental and Evolving Fuzzy ML Classifiers
• Big Data analysis through Fuzzy techniques

S9: Mathematical Fuzzy Logic

ORGANIZERS

• Tommaso Flaminio (Artificial Intelligence Research Institute of Bellaterra, Spain)
• Brunella Gerla (University of Insubria, Italy)
• Vilém Novák (University of Ostrava, Czech Republic)

SCOPE

The study of logical, algebraic and proof theoretical tools for the management of vagueness and uncertainty is a well-established line of research, whose development has significantly influenced many areas of applied research, from Economics and Game Theory to Artificial Intelligence. This special session, expression of the EUSFLAT working group of mathematical fuzzy logic, aims at collecting papers about (1) formal approaches to the theories of vagueness, uncertainty and imprecise information management that can be treated in the realm of many-valued logics and (2) extensions of MFL towards development of special theories modeling human reasoning.

It is focused on (but is not limited to) the following topics:

• Algebraic structures of many-valued logics
• Proof theory of many-valued logics
• Uncertainty theories on many-valued logics
• Game semantics of many-valued logics
• Topological and categorical methods for many-valued logics
• Fuzzy Natural Logic: Logical approaches to models of natural human reasoning

We also encourage the submission of papers on the use of algebraic and logical methods for applications in AI and elsewhere.

S10: Pre-aggregation functions and generalized forms of monotonicity

ORGANIZERS

• Humberto Bustince (Universidad Pública de Navarra, Spain)
• Javier Fernández (Universidad Pública de Navarra, Spain)
• Graçaliz Dimuro (Universidade Federal do Rio Grande, Brazil)
• Radko Mesiar (Slovak University of Technology, Slovakia)
• Tomasa Calvo (Universidad de Alcalá, Spain)

SCOPE

This special session is aimed at discussing the most recent theoretical developments related to fusion functions satisfying some generalized forms of monotonicity. In particular, the session in dedicated to weaker forms of monotonicity, e.g., directional monotonicity and ordered directional monotonicity. Then, the session will focus on generalizations of the concept of aggregation functions when one consider some generalized forms of monotonicity, e.g., pre-aggregation functions and pre-classes of functions. Pre-aggregation functions have appeared in the literature in 2016 and, since then, the interest on new classes of functions derived by pre-aggregation functions has increased a lot. Such functions encompass both classical aggregation functions and other weaker functions that do not fulfil the full monotonicity condition, but present excellent behavior in aggregation processes, so offering more flexibility in applications. In this sense, the objective of this session is to provide researchers in the field with an opportunity to present their most recent developments and to discuss recent trends in this area, as well as to identify potential problems of interest for researchers.

The following is a non-exhaustive list of topics that this session intends to cover:

• Directional monotonicity
• Weak monotonicity
• Ordered directional monotonicity
• Pre-aggregation functions
• Pre-classes of functions

S11: Applications of pre-aggregation functions

ORGANIZERS

• Humberto Bustince (Universidad Pública de Navarra, Spain)
• Graçaliz Dimuro (Universidade Federal do Rio Grande, Brazil)
• Benjamín Bedregal (Universidade Federal do Rio Grande do Norte, Brazil and Universidad Pública de Navarra, Spain)
• Radko Mesiar (Slovak University of Technology, Slovakia)

SCOPE

This special session is dedicated to discuss the potential applications of pre-aggregation functions and other classes of aggregation-like functions satisfying weaker monotonicity conditions, e.g., directional monotonicity and ordered directional monotonicity. The main concept in the field, namely, pre-aggregation functions, have appeared in the literature in 2016, in the context of classification problems, replacing classical aggregation operators used in the fuzzy reasoning mechanism of fuzzy rule-based systems (FRBS). The excellent performance provided by pre-aggregation functions in FRBSs have increased the interest of the researchers in their use in other kinds of applications that require some kind aggregation process but the full standard monotonicity may be not required, like image processing and deep learning. Also, their use in real classification problems are appearing in the literature. Then, the objective of this session is to provide researchers in the field with an opportunity to present their most recent developments in applications and to discuss recent trends in this area, as well as to identify potential application problems of interest for researchers.

The following is a non-exhaustive list of topics that this session intends to cover:

• Applications of pre-aggregation functions in classification problems
• averaging and no-averaging pre-aggregation functions in applications
• applications of pre-aggregation functions in image processing
• application of pre-aggregation functions in deep learning
• real case studies
• application of pre-classes of functions
• applications of ordered directional monotonic functions

S12: Special Session on Fuzzy Logic Applications for the Digital Economy and Society

ORGANIZERS

• Edy Portmann (University of Fribourg, Switzerland)
• Luis Terán (Universidad de las Fuerzas Armadas ESPE, Ecuador)

SCOPE

With today’s information overload, it has become increasingly difficult to analyze the huge amounts of data and to generate appropriate management decisions. Furthermore, the data are often imprecise and will include both quantitative and qualitative elements. For these reasons it is important to extend traditional decision making processes by adding intuitive reasoning, human subjectivity and imprecision. In the age of Big Data, decision making processes for economy and society have to deal with uncertainty, vagueness, and imprecision. Besides Volume, Variety and Velocity, two others V’s for Veracity and Value have also to be taken into consideration. Therefore, the application of fuzzy sets and fuzzy logic becomes a hot topic.

The Special Session that is part of the 11th Conference of the European Society for Fuzzy Logic and Technology will address the application of fuzzy logic to managerial decision making processes. Research papers as well as case studies are of interest in the following areas:

• Fuzzy-based Portfolio Analysis
• Reputation Management with Imprecision
• Web Analytics with Fuzzy Measures
• Fuzzy-based Business Analytics
• Inductive Fuzzy Classification
• Community Marketing with Fuzzy Methods
• Fuzzy-based Customer Equity
• Service Level Management with Vague Data
• Data Mining with Fuzziness
• Fuzzy-based Stakeholder Management
• Customer Relationship Management with Fuzzy Methods
• Fuzzy Cognitive Maps for Creativity and Knowledge Management
• Business (Process) Modeling with Words
• Sense-making with Vague (Web) Data
• Political participation and fuzzy voting
• Fuzzy-based eHealth Applications
• and related topics

S13: Aggregation functions: recent trends and developments, and applications

ORGANIZERS

• Humberto Bustince (Universidad Pública de Navarra, Spain)
• Radko Mesiar (Slovak University of Technology, Slovakia)
• Tomasa Calvo (Universidad de Alcalá, Spain)

SCOPE

Aggregation functions are nowadays a basic tool for any procedure where the fusion of information is required. In recent times, the interest and the work in this field is rapidly growing and have led to a deep study of not only classical aggregation functions such as weighted means, t-norms or t-conorms, but also of others such as those constructed by means of Choquet or Sugeno integrals, copulas, overlap and grouping functions or ignorance functions, among many others, as well as of generalizations of the notion of aggregation function, as it is the case of pre-aggregation functions. All these developments have been closely linked to an increasing number of applications in many different topics, from image processing to classification, machine learning or decision making, just to mention a few of them.

The aim of this special session is to bring researchers in the field of Aggregation Functions, to exchange their ideas and approaches, to discuss and to present latest results on this field, both from a theoretical and an applied point of view. In this way, it will follow the rich tradition of Special Sessions in Aggregation Functions from previous EUSFLAT Conferences.

Theoretical aspects:

• Properties of aggregation functions
• Generalizations of the idea of aggregation function
• Copulas and triangular norms
• Fuzzy measures and integrals
• Averaging aggregation operators
• Aggregations with ordinal and nominal scales
• Aggregation functions for extensions of fuzzy sets
• Aggregation on particular lattices

Practical aspects:

• Security intelligence, analysis and decision support
• Evaluation problems
• Medical decision problems
• Hybrid intelligent systems and computational intelligence
• Approximate reasoning
• Image processing
• Model identification and parametrization
• Diagnostics and prognostics
• Data mining

S14: Soft Models in Probability and Statistics

ORGANIZERS

• Przemyslaw Grzegorzewski (Polish Academy of Sciences and Warsaw University of Technology, Poland)
• Maria Brigida Ferraro (University of Rome, Italy)
• Ana Belén Ramos Guajardo (Universidad de Oviedo, Spain)
• Pedro Terán (Universidad de Oviedo, Spain)

SCOPE

Wide range of applications reveals the need for a more flexible modelling of imprecision, uncertainty, vagueness and ignorance. The proposed new methods are softer than the traditional theories and techniques because being less rigid they more easily adapt to the actual nature of information. For example, integrating fuzzy sets and probability can lead to more robust and interpretable models and tools in data analysis and data mining which better capture all kinds of the information contained in data. Also, in science and engineering the need to analyze and model the true uncertainty associated with complex systems requires a more sophisticated representation of ignorance than that provided by uninformative Bayesian priors.

The aim of this Special Session is to bring together theoreticians and practitioners working on soft probability, statistics and data analysis for exchanging ideas and discussing new trends that enlarge the statistical and uncertainty modelling traditions, towards a flexible and more specific handling of incomplete or subjective information.

Topics of interest include, but are not limited to:

• Analysis of Censored Data
• Analysis of Fuzzy Data
• Clustering and Classification
• Dempster-Shafer Theory
• Fuzzy Random Variables
• Fuzzy Regression Methods
• Graphical Models
• Imprecise Probabilities
• Interval data
• Machine Learning
• Possibility Theory
• Random Sets/Random Fuzzy Sets
• Robust Statistics
• Rough Sets in Data Analysis
• Soft Computing and Statistics
• Statistical Software for Imprecise Data
• Triangular Norms and Copulas

S15: Workshop on Quantum Structures

ORGANIZERS

• Roberto Leporini (University of Bergamo, Italy)
• Mirko Navara (Czech Technical University in Prague, Czech Republic)
• Milan Petrík (Czech University of Life Sciences, Czech Republic)
• Jaroslaw Pykacz (Institute of Mathematics, University of Gdansk, Poland)
• Sandro Sozzo (University of Leicester, UK)

SCOPE

The workshop is oriented to the study of structures based on quantum mechanics, in its physical, mathematical, philosophical, applied, and interdisciplinary aspects.
The workshop is organized jointly with the International Quantum Structures Association (IQSA) as its meeting in 2019.
Members of IQSA are particularly encouraged to attend, but participation is not limited to the members of IQSA and all scientists interested in the above topics are welcome.

It is focused on (but is not limited to) the following topics:

• convex structures,
• logico-algebraic structures,
• orthomodular structures,
• quantum logics,
• empirical logics,
• operational structures,
• realistic structures,
• quantum measurement,
• quantum geometry,
• quantum statistics,
• quantum probability,
• quantum topology,
• quantum space time,
• quantum set theory,
• quantum information,
• quantum communication,
• quantum computation,
• fuzzy quantum logics.

Contributions combining fuzzy set ideas with quantum structures are specially welcome.

S16: Perspectives and challenges in data aggregation

ORGANIZERS

• Bernard De Baets (Ghent University, Belgium)
• Raúl Pérez-Fernández (University of Oviedo, Spain; Ghent University, Belgium)

SCOPE

The increasing exposure and quick dissemination of scientific results has facilitated to put in contact fields that have historically worked separately on similar problems. Precisely, aggregation problems have been addressed independently by, for instance, mathematicians and statisticians (aggregation of real numbers), computer scientists and bioinformaticians (aggregation of strings) or political scientists and economists (aggregation of rankings). The field of data aggregation, which is now witnessing a golden age due to the accessibility of large databases in the internet era, must take the challenge of bringing together centuries of impressive work spread over countless scientific fields. In particular, this special session aims at providing a forum for incentivating fruitful discussions on topics of potential interest to the field of data aggregation, both from theory and applications and even from an algorithmic point of view.

Topics of interest to this session include but are not limited to:

• Theory: aggregation on different types of structures, penalty and deviation functions, optimization challenges in data aggregation, ...
• Applications: decision making, social choice, pattern recognition, bioinformatics, ...
• Algorithms: analysis of computational complexity, approximation techniques, ...

S17: Soft Social Computing and Network Science

ORGANIZERS

• Nadezhda Yarushkina (Ulyanovsk State Technical University, Russian Federation)
• Alexander Tulupiev (Russian Academy of Sciences, Russian Federation)
• irina Perfilieva (University of Ostrava, Czech Republic)

SCOPE

The Special Session will be focused on theoretical and application aspects of social and networking analysis in general and advantage of fuzzy, Bayesian networks, and related models (soft computing) techniques in this field in particular. The objective of this special session is to present original developments that are useful in any application of social networking analysis, going from social network processing techniques to more complex aspects of Opinion Mining and Social Network dynamics understanding, defense against Social Engineering Attacks, Human Reliability analysis.

Social computing is an important and active field of research using tools and results from fuzzy natural language processing theory, linguistics, fuzzy ontologies, fuzzy graphs, fuzzy time series forecasting, Bayesian belief networks, algebraic Bayesian networks as well as other fields. Nowadays, one can find several approaches to Social Soft Computing. Hence, there is a need to compare and/or unite these approaches and possibly formulate a new perspective of research in Social Soft Computing and networking analysis.

Topics:

• Topics include, but are not limited to:
• Fuzzy systems in social network analysis,
• Fuzzy ontology in opinion mining,
• Soft computing techniques in text processing for social network analysis,
• Soft computing techniques in emotions processing for social network analysis
• Fuzzy approaches, Bayesian belief networks, algebraic Bayesian networks, and related probabilistic graphical models in social computing,
• Soft computing models and techniques in Social Engineering Attacks prevention, Human Reliability analysis, Network Science
• Fuzzy natural language processing in social network analysis,
• Fuzzy graphs in social network analysis,
• Fuzzy time series forecasting in Social Network dynamics analysis

S18: Fuzzy Implication Functions

ORGANIZERS

• Michal Baczynski (University of Silesia, Poland)
• Balasubramaniam Jayaram (Indian Institute of Technology Hyderabad, India)
• Sebastia Massanet (University of the Balearic Islands, Spain)

SCOPE

In recent years, fuzzy implication functions have become one of the main research lines of the fuzzy logic community. These logical connectives are the generalization of the classical two-valued implication to the infinite-valued setting. In addition of modelling fuzzy conditionals, they are also used to perform backward and forward inferences in different fuzzy rules based systems. Moreover, they have proved to be useful not only in fuzzy control and approximate reasoning, but also in many other fields like Multi-Valued Logic, Image Processing, Data Mining, Computing with Words and Rough Sets, among others.

Due to this great quantity of applications, fuzzy implication functions have attracted the efforts of many researchers also from the theoretical perspective focusing on problems whose solutions provide important insights from the point of view of their applications. Therefore, this special session seeks to bring together researchers interested in recent advances in the theory of fuzzy implication functions, concerning, among others, characterizations, representations, generalizations and their relationships with fuzzy negations, triangular norms, uninorms and other fuzzy logic connectives.

S19: Soft Computing on the Web

ORGANIZERS

• Jesús Serrano-Guerrero (Spain)
• José Angel Olivas (Spain)
• Francisco P. Romero (Spain)

SCOPE

In the current global Information Technology scenario, voluminous information from sources like webpages, blogs, social networks, or digital libraries among others, is available for processing. For this reason, new Information Retrieval, Decision Making and Recommender Systems more and more powerful are necessary nowadays; and related to this issue, new fields are emerging like Sentiment Analysis.

Sentiment Analysis/Opinion Mining studies the extraction of opinions or sentiments based on mainly Information Retrieval, Natural Language Processing and Artificial Intelligence, especially, since the information treated is heterogeneous in nature and lack in precision and completeness. Traditional systems are incompetent to handle these data, therefore, advanced techniques like proposed by Soft Computing (Fuzzy Logic, Neuro-computing, Probabilistic Reasoning, Evolutionary Computation, etc.) are necessary.

This special session on “Soft Computing on the Web” provides a forum to show original research works and real applications mainly related to possible uses of Soft Computing techniques for extracting, inferring, modeling, representing and handling information from heterogeneous sources like Internet.

Potential topics of interest include but are not limited to:

• Sentiment analysis/Opinion mining
• Emotion detection
• Search/meta search engines
• Semi or unstructured information representation/modeling
• Ontologies
• Multi-Lingual and cross-Lingual Issues
• Recommender systems
• Social networks
• Decision making
• Digital libraries

S20: Uncertainty in Sentiment-oriented Analysis of Reviews and Comments: from Products to Social Media

ORGANIZERS

• Matteo Gaeta (University of Salerno, Italy)
• Giuseppe D’Aniello (University of Salerno, Italy)
• Marek Reformat (University of Alberta, Canada)

SCOPE

Users participation in activities leading to expressing their points of views and comments regarding variety of topics is growing every day. At the same time, many people, companies, and organizations are very interested in knowing what users say. On many occasions, it leads to modifications of talked about items, finding solutions to identified issues, and influencing decision-making. A textual format of those comments, as well as ambiguity and imprecision of human’s expressions mean that a correct interpretation of textual statements and determining users’ opinions, emotions, and reactions is very important.

Fuzzy Logic and Soft Computing provide significant and non-trivial approaches, techniques and methods suitable for dealing with imprecision, identification of humans’ emotions, aggregation of multiple sources of information, or summarization of gathered options. It is anticipated, that applications of Fuzziness and Soft Computing technologies will bring a new way of performing tasks related to processing reviews/comments and determining final sentiments and judgments embedded in them.

The special session will focus on the current research trends in the area of theory and practical aspects of text processing techniques built based on/with fuzzy and other soft computing methods suitable for addressing issues specific for aspect-based sentiment analysis.

The topics of particular interest, that are addressed with Fuzziness and Soft Computing approaches, include but are not limited to:

• natural language processing
• semantic-based processing of text
• fuzzy ontology and ontology-based text analysis
• knowledge- and rule- based systems for opinion identification
• fuzzy based techniques for sentiment recognition
• soft-computing methods for aspect identification
• sentiment-based recommender systems
• soft and hard data fusion for social media analytics
• sentiment analysis for Smart City and e-Government
• opinion-driven decision making and approximate reasoning
• applications for social media analytics

S21: Fuzzy transforms: theory and applications to data analysis and image processing

ORGANIZERS

• Irina Perfilieva (University of Ostrava, Czech Republic)
• Luciano Stefanini (University of Urbino ”Carlo Bo”, Italy)
• Svetlana Asmuss (University of Latvia, Latvia)

SCOPE

Fuzzy (F)-transforms successfully link various transforms (Fourier, Laplace, integral, Wavelet, etc.) with fuzzy approximation models. The general idea is to bring an original model into a special space where succeeding computations are easier. In particular, the F-transform transforms an infinitary object (a real function) into a finitary one (a finite vector). Another specific feature of the F-transform consists in including a fuzzy partition in its formal representation.

The session will be focused on new directions in the development of the F-transform theory. They are based on recent results regarding approximation properties of the direct and inverse F-transform in Lp spaces and some particular Sobolev spaces. In parallel, the lattice-based F-transform, where the approximation is estimated in terms of the lattice order, will be discussed as well.

In image and signal processing, the F-transform effectively solves problems connected with dimensionality reduction and preprocessing of big data.

Objectives and topics:

The aim of this special session is to present recent developments and trends in the theory and applications of the F-transform, including all mentioned above. Beside theoretical aspects, the session will be focused on advanced applications in data analysis including handling big data. We invite contributions that extend traditional ways of data analysis and propose adequate methods for various kinds of data processing including, but not limited to the following topics:

• Theoretical aspects of the F-transform and its higher degree versions,
• Inverse F-transform and how to improve its approximation quality,
• Numerical methods on the basis of F-transform,
• F-Transform and Aggregation Operators,
• Big data processing on the basis of the F-transform,
• Applications to Image Processing and Computer Vision,
• Time series analysis and forecasting.

S22: Soft Computing Techniques in Image Processing

ORGANIZERS

• Irina Perfilieva (University of Ostrava, Czech Republic)
• Javier Montero (Complutense University of Madrid, Spain)
• Carlos Lopez-Molina (Public University of Navarre, Spain)

SCOPE

The Special Session will be focused on theoretical and application aspects of image processing. In particular, the special interest will be paid to modern methods that combine sophisticated conventional, fuzzy and neural network techniques together. The main topics of interest are the following:

• Image preprocessing
• Image features extraction
• Pattern matching and recognition on images
• Image fusion
• Image reconstruction and inpainting
• Image compression
• Edge detection
• Registration
• Segmentation

With applications to:

• Computer vision
• Medical imaging
• Agriculture and Earth monitoring
• Image processing on wearable devices

S23: Fuzzy dynamical systems

ORGANIZERS

• Jan Andres (Palacky University in Olomouc, Czech Republic)
• Jiří Kupka (University of Ostrava, Czech Republic)
• Xinxing Wu (Southwest Petroleum University, P.R. China)

SCOPE

Topological dynamics is a well established field of mathematics in which the main object of study is a topological dynamical system, i.e., a topological space with a continuous self-transformation on that space. This field was established approximately one hundred years ago by G. Birkhoff’s studies of recurrence, and nowadays it covers many subfields like symbolic dynamics, ergodic theory, chaos theory and others. And in the last decades several natural directions combining studies in topological dynamics and fuzzy mathematics have appeared.

The purpose of this special session is to bring together researchers interested in theory and also possible applications of fuzzy (dynamical) systems and related topics. Here a fuzzy topological dynamical system could be the one which is induced by Zadeh’s extension principle from a given crisp (non-fuzzy) topological dynamical system, but related constructions and approaches are welcome too. Although the title of this special session is about fuzzy dynamical systems, we also welcome contributions on relevant results from non-fuzzy community, for instance, on dynamical properties of multi-valued, set-valued or iterated dynamical systems (IFSs).

Consequently, topics of interest include, but are not limited to, the following topics:

• induced (set-valued) dynamical systems
• fuzzy dynamical systems
• dynamical systems with uncertainty
• fractal theory
• fixed point theory
• fuzzy topology
• fuzzy number theory
• iterated and multi-valued dynamical systems

S24: Fuzzy mathematical analysis and its applications

ORGANIZERS

• Yurilev Chalco-Cano
• Alireza Khastan
• Juan Carlos Figueroa G.

SCOPE

Mathematical analysis, in the broad sense of the term, includes a very large part of mathematics. It includes the theory of functions of a real variable, differential calculus; integral calculus; approximation theory; the theory of ordinary and partial differential equations, the theory of integral equations. On the other hand, fuzzy mathematics forms a branch of mathematics related to fuzzy set theory and fuzzy logic. Fuzzy mathematical analysis appears as one of the natural ways to study the uncertainties in related concepts of mathematical analysis. In the recent years, the concepts of fuzzy metric space, fuzzy integral and derivative, fuzzy initial value problem have been proposed. The goal of this session is to bring together researchers interested in recent advances in fuzzy mathematical analysis and its applications.

The topics of this special session include, but are not limited to, the following:

• Spaces of fuzzy sets
• Fuzzy arithmetic
• Fuzzy metric spaces
• General fuzzy-valued functions
• Convexity and fuzzy-valued functions
• Differentiability of fuzzy-valued functions
• Fuzzy integrals
• Fuzzy differential equations
• Fuzzy partial differential equations
• Fuzzy optimal control
• Fuzzy systems
• Fuzzy optimization problems

S25: Inter-Relation Between Interval and Fuzzy Techniques

ORGANIZERS

• Martine Ceberio (University of Texas at El Paso, USA)
• Vladik Kreinovich (University of Texas at El Paso, USA)

SCOPE

The relation between fuzzy and interval techniques is well known; e.g., due to the fact that a fuzzy number can be represented as a nested family of intervals (alpha-cuts), level-by-level interval techniques are often used to process fuzzy data.

At present, researchers in fuzzy data processing mainly used interval techniques originally designed for non-fuzzy applications, techniques which are often taken from textbooks and are, therefore, already outperformed by more recent and more efficient methods.

One of the main objectives of the proposed special session is to make the fuzzy community at-large better acquainted with the latest, most efficient interval techniques, especially with techniques specifically developed for solving fuzzy-related problems.

Another objective is to combine fuzzy and interval techniques, so that we will be able to use the combined techniques in (frequent) practical situations where both types of uncertainty are present: for example, when some quantities are known with interval uncertainty (e.g., coming from measurements), while other quantities are known with fuzzy uncertainty (coming from expert estimates).