Bøger i Fuzzy Management Methods serien

This book introduces a novel type of expert finder system that can determine the knowledge that specific users within a community hold, using explicit and implicit data sources to do so.

Successful interaction between humans and artificial systems allows for combining the advantages of all actors in solving problems. However, interaction is often demanding for people, as it builds on artificial concepts, such as strict protocols.This book presents the new paradigm of 'phenotropic' interaction, which aims to improve the naturalness of the interaction thanks to bio-inspired approaches. These include methods for understanding and reasoning with human perceptions expressed as natural language, fundamental to support the artificial system to better understand people's real desires and needs. Methods for improving the theories of computing with words and perceptions are developed in this book and applied to concrete use cases in prototypes enhancing the exchange of information with virtual assistants and smart city ecosystems. The presented use cases serve not only as examples of the application of the phenotropic interaction principles but also to verify their effective impact on communication.

Last-mile delivery in cities, where the main problems are the traffic situation and ensuring access to customers' homes while maintaining their privacy, poses a substantial logistical challenge. This book explores how the service area of mobility, especially last-mile delivery, can be improved and smartified. It demonstrates how a design science method and a transdisciplinary approach have been used to create a traffic area analysis tool that can accommodate the uncertainty and incompleteness of geospatial data; a linguistic traffic merging tool; and a customer classifier. In terms of developing the optimization artifacts, the socio-economic and logistical aspects of cities were considered and fuzzy logic and nature-inspired swarm intelligence (fuzzy ant colony optimization) were applied as basic principles.   Pursuing a transdisciplinary approach, the book offers both practical know-how from the industry and theoretical findings, making it a valuable asset for researchers and practitioners in the fields of mobility and logistics.

This book presents the concept of a fuzzy-based recommender system for user account privacy settings that can be used for citizen participation on online political platforms. The elaborated components are exemplarily based on the needs of a political platform implemented during the presidential election in Ecuador. The book readdresses the issue of privacy paradox demonstrating that, indeed, users' actual decisions of being private in most cases diverge with their initial privacy intentions. The two concepts presented in the book - the citizen privacy profile framework and the prototype fuzzy-based privacy settings recommender system - can be adapted by different organizations such as government institutions, NGOs, or private online service providers to meet their specific needs.   The book will be of interest to researchers and practitioners in the areas of usage modeling, privacy, system design, and for service providers in eDemocracy.

Fuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems.This book presents a novel algorithm called glassoFCM to enable automatic learning of FCM models from data.

The main focus of this book is on presenting advances in fuzzy statistics, and on proposing a methodology for testing hypotheses in the fuzzy environment based on the estimation of fuzzy confidence intervals, a context in which not only the data but also the hypotheses are considered to be fuzzy.

Electronic participation is an emerging and growing research area that makes use of internet solutions to enhance citizens' participation in government processes in order to provide a fair and efficient society.

Using computers to simulate human intelligence with fuzzy approaches is the basis of "Fuzzy-AI model," which offers an efficient tool capable of simulating human intelligence in order to perform digitized decision inference and quantitative information management

This edited book presents the state-of-the-art of applying fuzzy logic to managerial decision-making processes in areas such as fuzzy-based portfolio management, recommender systems, performance assessment and risk analysis, among others.

This book examines how fuzzy methods can be employed to manage service levels in business and IT alignment. It starts by mapping the dependencies of service level agreements, coming up with gradual and bi-polar concepts to eventually classify the level of coupling by intuitionistic fuzzy sets.

This book addresses the latest research and applications of fuzzy management methods for business decisions. how fuzzy management methods support the inclusion of human thinking and human behavior in decision making processes; how to generate better results with fuzzy management methods in cases of imprecise information;

This book introduces a fuzzy classification approach, which combines relational databases with fuzzy logic for more effective and powerful customer relationship management (CRM). The book starts with a presentation of the basic concepts, fuzzy set theory and the combination of relational databases and fuzzy classification.

In this book a fuzzy-based recommender system architecture for stimulating political participation and collaboration is proposed. It showcases the "Smart Participation" project, which uses the database of "smart vote", a well-known voting advice application (VAA) for local, cantonal and national elections in Switzerland.

Based on practical experience as a data analyst and on theoretical studies as a researcher, the author explains fuzzy classification, inductive logic and the concept of likelihood and introduces a blend of Bayesian and Fuzzy Set approaches, allowing reasonings on fuzzy sets that are derived by inductive logic.

The numeric values retrieved from a data warehouse may be difficult for business users to interpret, and may even be interpreted incorrectly. Moreover, it introduces a modeling approach for fuzzy data warehouses that makes it possible to integrate fuzzy linguistic variables in a meta-table structure.

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product.