This volume showcases contributions from internationally-known researchers in the field of information management. Most of the approaches presented here make use of fuzzy logic, introduced by L.A. Zadeh almost 50 years ago, which constitute a powerful tool to model and handle gradual concepts. What all of these contributions have in common is placing the user at the center of the information system, be it for helping him/her to query a data set, to handle imperfect information, or to discover useful knowledge from a massive collection of data. Researchers working in data and knowledge management will greatly benefit from this collection of up-to-date studies. This may be also an invaluable source of information for postgraduate students interested in advanced information management techniques.

This book constitutes the refereed proceedings of the 11th International Conference on Scalable Uncertainty Management, SUM 2017, which was held in Granada, Spain, in October 2017. The 24 full and 6 short papers presented in this volume were carefully reviewed and selected from 35 submissions. The book also contains 3 invited papers. Managing uncertainty and inconsistency has been extensively explored in Artificial Intelligence over a number of years. Now, with the advent of massive amounts of data and knowledge from distributed, heterogeneous, and potentially conflicting sources, there is interest in developing and applying formalisms for uncertainty and inconsistency in systems that need to better manage this data and knowledge. The International Conference on Scalable Uncertainty (SUM) aims to provide a forum for researchers who are working on uncertainty management, in different communities and with different uncertainty models, to meet and exchange ideas.

This volume contains the papers presented at the Eleventh Flexible Query Answering Systems 2015 (FQAS-2015) held on October 26-28, 2015 in Cracow, Poland. The international conferences on Flexible Query Answering Systems (FQAS) are a series of premier conferences focusing on the key issue in the information society of providing easy, flexible, and intuitive access to information and knowledge to everybody, even people with a very limited computer literacy. In targeting this issue, the Conference draws on several research areas, such as information retrieval, database management, information filtering, knowledge representation, soft computing, management of multimedia information, and human-computer interaction. The Conference provides a unique opportunity for researchers, developers and practitioners to explore new ideas and approaches in a multidisciplinary forum.

This book constitutes the refereed proceedings of the 22nd International Symposium on Methodologies for Intelligent Systems, ISMIS 2015, held in Lyon, France, in October 2015. The 31 revised full papers presented together with 18 short papers were carefully reviewed and selected from 67 submissions. The papers are organized in topical sections on data mining methods; databases, information retrieval, recommender systems; machine learning; knowledge representation, semantic web; emotion recognition, music information retrieval; network analysis, multi-agent systems; applications; planning, classification; and textual data analysis and mining.

The manipulation of databases is an integral part of a world which is becoming increasingly and pervasively information-focused. This book puts forward a suggestion to advocate preference queries and fuzzy sets as a central concern in database queries and offers an important contribution to the design of intelligent information systems. It provides a comprehensive study on fuzzy preference queries in the context of relational databases. Preference queries, a recent hot topic in database research, provide a basis for rank-ordering the items retrieved, which is especially valuable for large sets of answers.This book aims to show that fuzzy set theory constitutes a highly expressive framework for modeling preference queries. It presents a study of the algorithmic aspects related to the evaluation of such queries in order to demonstrate that this framework offers a good trade-off between expressivity and efficiency. Numerous examples and proofs are liberally and lucidly demonstrated throughout, and greatly enhance the detailed theoretical aspects explored in the book.Researchers working in databases will greatly benefit from this comprehensive and up-to-date study of fuzzy preference queries, and it will also become an invaluable reference point for postgraduate students interested in advanced database techniques.The only other books which deal with this topic are edited books or conference proceedings which include a few contributions about some specific aspects of the question. This book provides a comprehensive view of the issue, starting with basic notions related to relational databases and fuzzy set theory, up to the detailed study of complex fuzzy queries and the way they can be efficiently processed. It is the compendium of more than 20 years of research by the authors who benefit from a great international recognition in the domain of intelligent information systems, on the subject.