Maria Vanina Martinez – författare

This SpringerBrief proposes a general framework for reasoning about inconsistency in a wide variety of logics, including inconsistency resolution methods that have not yet been studied.  The proposed framework allows users to specify preferences on how to resolve inconsistency when there are multiple ways to do so. This empowers users to resolve inconsistency in data leveraging both their detailed knowledge of the data as well as their application needs. The brief shows that the framework is well-suited to handle inconsistency in several logics, and provides algorithms to compute preferred options. Finally, the brief shows that the framework not only captures several existing works, but also supports reasoning about inconsistency in several logics for which no such methods exist today.

This SpringerBrief proposes a general framework for reasoning about inconsistency in a wide variety of logics, including inconsistency resolution methods that have not yet been studied.  The proposed framework allows users to specify preferences on how to resolve inconsistency when there are multiple ways to do so. This empowers users to resolve inconsistency in data leveraging both their detailed knowledge of the data as well as their application needs. The brief shows that the framework is well-suited to handle inconsistency in several logics, and provides algorithms to compute preferred options. Finally, the brief shows that the framework not only captures several existing works, but also supports reasoning about inconsistency in several logics for which no such methods exist today.

This book constitutes proceedings of the 18th European Conference on Logics in Artificial Intelligence, JELIA 2023, held in Dresden, Germany, in September 2023.The 41 full papers and 11 short papers included in this volume were carefully reviewed and selected from 111 submissions. The accepted papers span a number of areas within Logics in AI, including: argumentation; belief revision; reasoning about actions, causality, and change; constraint satisfaction; description logics and ontological reasoning; non-classical logics; and logic programming (answer set programming).

This book constitutes proceedings of the 18th European Conference on Logics in Artificial Intelligence, JELIA 2023, held in Dresden, Germany, in September 2023.The 41 full papers and 11 short papers included in this volume were carefully reviewed and selected from 111 submissions. The accepted papers span a number of areas within Logics in AI, including: argumentation; belief revision; reasoning about actions, causality, and change; constraint satisfaction; description logics and ontological reasoning; non-classical logics; and logic programming (answer set programming).

This book constitutes the refereed proceedings of the 17th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2024, held in Dallas, TX, USA, during October 11-14, 2024.The 27 full papers and  3 short papers included in this book were carefully reviewed and selected from 48 submissions. They deal with declarative logic programming, non-monotonic reasoning, and knowledge representation, focusing on the design and implementation of logic-based programming languages and database systems.

This book constitutes the refereed proceedings of the 16th International Conference on Scalable Uncertainty Management, SUM 2024, held in Palermo, Italy, during November 27–29, 2024.The 28 full and 7 short papers presented in this volume were carefully reviewed and selected from 43 submissions. SUM 2024 solicited three types of paper submissions: Long papers reporting on original research or providing surveys that synthesize current research trends, short papers describing promising work in progress, systems, or positions oncontroversial issues, and extended abstracts.

This SpringerBrief  reviews the knowledge engineering problem of engineering objectivity in top-k query answering; essentially, answers must be computed taking into account the user’s preferences and a collection of (subjective) reports provided by other users. Most assume each report can be seen as a set of scores for a list of features, its author’s preferences among the features, as well as other information is discussed in this brief. These pieces of information for every report are then combined, along with the querying user’s preferences and their trust in each report, to rank the query results. Everyday examples of this setup are the online reviews that can be found in sites like Amazon, Trip Advisor, and Yelp, among many others.Throughout this knowledge engineering effort the authors adopt the Datalog+/– family of ontology languages as the underlying knowledge representation and reasoning formalism, and investigate several alternative ways in which rankings can bederived, along with algorithms for top-k (atomic) query answering under these rankings. This SpringerBrief also investigate assumptions under which our algorithms run in polynomial time in the data complexity. Since this SpringerBrief contains a gentle introduction to the main building blocks (OBDA, Datalog+/-, and reasoning with preferences), it should be of value to students, researchers, and practitioners who are interested in the general problem of incorporating user preferences into related formalisms and tools.  Practitioners also  interested in using Ontology-based Data Access to leverage information contained in reviews of products and services for a better customer experience will be interested in this brief and  researchers working in the areas of Ontological Languages, Semantic Web, Data Provenance, and Reasoning with Preferences.