Dr. Zoumpolia Dikopoulou received the MSc degree in Computer Science from Ionian University, Corfu, Greece and was awarded with the academic degree of Doctor of Sciences: Computer Science from Hasselt University, Belgium. She is the author and co-author of scientific published papers, books and book chapters. In addition, she is a developer of the ‘fcm’ package in the R programming language. She has research experience working at various national and European projects and she currently works as a Senior data analyst at the AiDEAS company, Talin, Esthonia under the H2020 EU project. Finally, her research interests are focused on probabilistic graphical models, machine learning, graph theory, fuzzy cognitive maps, decision support systems and aggregation methods.

• Chapter 1. Introduction.- Chapter 2. Data Analysis.- Chapter 3. Fuzzy Cognitive Maps.- Chapter 4. Data Modeling.- Chapter 5. Network analysis, accuracy and stability of the job-satisfaction structures.- Chapter 6. The proposed data-driven glassoFCM method.- Chapter 7. Thesis Conclusions.

Dr. Zoumpolia Dikopoulou received the MSc degree in Computer Science from Ionian University, Corfu, Greece and was awarded with the academic degree of Doctor of Sciences: Computer Science from Hasselt University, Belgium. She is the author and co-author of scientific published papers, books and book chapters. In addition, she is a developer of the ‘fcm’ package in the R programming language. She has research experience working at various national and European projects and she currently works as a Senior data analyst at the AiDEAS company, Talin, Esthonia under the H2020 EU project. Finally, her research interests are focused on probabilistic graphical models, machine learning, graph theory, fuzzy cognitive maps, decision support systems and aggregation methods.

• Chapter 1. Introduction.- Chapter 2. Data Analysis.- Chapter 3. Fuzzy Cognitive Maps.- Chapter 4. Data Modeling.- Chapter 5. Network analysis, accuracy and stability of the job-satisfaction structures.- Chapter 6. The proposed data-driven glassoFCM method.- Chapter 7. Thesis Conclusions.

Dr. Zoumpolia Dikopoulou received the MSc degree in Computer Science from Ionian University, Corfu, Greece and was awarded with the academic degree of Doctor of Sciences: Computer Science from Hasselt University, Belgium. She is the author and co-author of scientific published papers, books and book chapters. In addition, she is a developer of the ‘fcm’ package in the R programming language. She has research experience working at various national and European projects and she currently works as a Senior data analyst at the AiDEAS company, Talin, Esthonia under the H2020 EU project. Finally, her research interests are focused on probabilistic graphical models, machine learning, graph theory, fuzzy cognitive maps, decision support systems and aggregation methods.

• Chapter 1. Introduction.- Chapter 2. Data Analysis.- Chapter 3. Fuzzy Cognitive Maps.- Chapter 4. Data Modeling.- Chapter 5. Network analysis, accuracy and stability of the job-satisfaction structures.- Chapter 6. The proposed data-driven glassoFCM method.- Chapter 7. Thesis Conclusions.