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Author: G. Cima
Publisher: IOS Press
ISBN: 1643682598
Category : Computers
Languages : en
Pages : 270
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Book Description
Effectively documenting data services is a crucial issue in any organization, not only for governing data but also for interoperation purposes. Indeed, in order to fully realize the promises and benefits of a data-driven society, data-driven approaches need to be resilient, transparent, and fully accountable. This book, Abstraction in Ontology-based Data Management, proposes a new approach to automatically associating formal semantic description to data services, thus bringing them into compliance with the FAIR (Findable, Accessible, Interoperable, and Reusable) guiding principles. The approach is founded on the Ontology-based Data Management (OBDM) paradigm, in which a domain ontology is used to provide a high-level semantic layer mapped to the source schema of an organization containing data, thus abstracting from the technical details of the data layer implementation. A formal framework for a novel reasoning task in OBDM, called Abstraction, is introduced in which a data service is assumed to be expressed as a query over the source schema, and the aim is to derive a query over the ontology that semantically describes the given data service best with respect to the underlying OBDM specification. In a general scenario that uses the most popular languages in the OBDM literature, an in-depth complexity analysis of two computational problems associated with the framework is carried out. Also investigated is the problem of expressing abstractions in a non-monotonic query language as well as the impact of adding inequalities. Regarding the latter, the problem of answering queries with inequalities over lightweight ontologies is first studied. Lastly, the author illustrates how the achieved results contribute to new results in the Semantic Web context and in the Relational Database theory. The book will be of interest to all those engaged in Artificial Intelligence and Data Management.
Author: G. Cima
Publisher: IOS Press
ISBN: 1643682598
Category : Computers
Languages : en
Pages : 270
Get Book Here
Book Description
Effectively documenting data services is a crucial issue in any organization, not only for governing data but also for interoperation purposes. Indeed, in order to fully realize the promises and benefits of a data-driven society, data-driven approaches need to be resilient, transparent, and fully accountable. This book, Abstraction in Ontology-based Data Management, proposes a new approach to automatically associating formal semantic description to data services, thus bringing them into compliance with the FAIR (Findable, Accessible, Interoperable, and Reusable) guiding principles. The approach is founded on the Ontology-based Data Management (OBDM) paradigm, in which a domain ontology is used to provide a high-level semantic layer mapped to the source schema of an organization containing data, thus abstracting from the technical details of the data layer implementation. A formal framework for a novel reasoning task in OBDM, called Abstraction, is introduced in which a data service is assumed to be expressed as a query over the source schema, and the aim is to derive a query over the ontology that semantically describes the given data service best with respect to the underlying OBDM specification. In a general scenario that uses the most popular languages in the OBDM literature, an in-depth complexity analysis of two computational problems associated with the framework is carried out. Also investigated is the problem of expressing abstractions in a non-monotonic query language as well as the impact of adding inequalities. Regarding the latter, the problem of answering queries with inequalities over lightweight ontologies is first studied. Lastly, the author illustrates how the achieved results contribute to new results in the Semantic Web context and in the Relational Database theory. The book will be of interest to all those engaged in Artificial Intelligence and Data Management.
Author: Setsuo Ohsuga
Publisher: IOS Press
ISBN: 9789051990737
Category : Artificial intelligence
Languages : en
Pages : 726
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Book Description
Papers direct the focus of interest to the development and use of conceptual models in information systems of various kinds and aim at improving awareness about general or specific problems and solutions in conceptual modelling.
Author: Marisa Faggini
Publisher: Springer Science & Business Media
ISBN: 8847017785
Category : Mathematics
Languages : en
Pages : 252
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Book Description
In economics agents are assumed to choose on the basis of rational calculations aimed at the maximization of their pleasure or profit. Formally, agents are said to manifest transitive and consistent preferences in attempting to maximize their utility in the presence of several constraints. They operate according to the choice imperative: given a set of alternatives, choose the best. This imperative works well in a static and simplistic framework, but it may fail or vary when 'the best' is changing continuously. This approach has been questioned by a descriptive approach that springing from the complexity theory tries to give a scientific basis to the way in which individuals really choose, showing that those models of human nature is routinely falsified by experiments since people are neither selfish nor rational. Thus inductive rules of thumb are usually implemented in order to make decisions in the presence of incomplete and heterogeneous information sets.
Author: Jyrki Nummenmaa
Publisher: Springer Nature
ISBN: 303033614X
Category : Technology & Engineering
Languages : en
Pages : 371
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Book Description
This book presents the proceedings of the Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2019), held in Ambato in October 2019, with participants from 13 countries and guest speakers from Chile, Colombia, France, Japan, Spain, Portugal, and United States. Featuring 23 peer-reviewed papers, it discusses topics such as the use of metaheuristic for non-deterministic problem solutions, software architectures for supporting e-government initiatives, and the use of electronics in e-learning and industrial environments. It also includes contributions illustrating how new approaches on these converging research areas are impacting the development of human societies around the world into Society 5.0. As such, it is a valuable resource for scholars and practitioners alike.
Author: Gerardo I. Simari
Publisher: Springer
ISBN: 331965229X
Category : Computers
Languages : en
Pages : 83
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Book Description
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 b e derived, 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.
Author: M. Hecher
Publisher: IOS Press
ISBN: 1643683454
Category : Computers
Languages : en
Pages : 252
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Book Description
This book, Advanced Tools and Methods for Treewidth-Based Problem Solving, contains selected results from the author’s PhD studies, which were carried out from 2015 to 2021. For his PhD thesis, Markus Hecher received the EurAI Dissertation Award 2021 and the GI Dissertation Award 2021, amongst others. The aim of the book is to present a new toolkit for using the structural parameter of treewidth to solve problems in knowledge representation and reasoning (KR) and artificial intelligence (AI), thereby establishing both theoretical upper and lower bounds, as well as methods to deal with treewidth efficiently in practice. The key foundations outlined in the book provide runtime lower bounds – under reasonable assumptions in computational complexity – for evaluating quantified Boolean formulas and logic programs which match the known upper bounds already published in 2004 and 2009. The general nature of the developed tools and techniques means that a wide applicability beyond the selected problems and formalisms tackled in the book is anticipated, and it is hoped that the book will serve as a starting point for future theoretical and practical investigations, which will no doubt establish further results and gain deeper insights.
Author: T. Schaub
Publisher: IOS Press
ISBN: 1614994196
Category : Computers
Languages : en
Pages : 1264
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Book Description
The role of artificial intelligence (AI) applications in fields as diverse as medicine, economics, linguistics, logical analysis and industry continues to grow in scope and importance. AI has become integral to the effective functioning of much of the technical infrastructure we all now take for granted as part of our daily lives. This book presents the papers from the 21st biennial European Conference on Artificial Intelligence, ECAI 2014, held in Prague, Czech Republic, in August 2014. The ECAI conference remains Europe's principal opportunity for researchers and practitioners of Artificial Intelligence to gather and to discuss the latest trends and challenges in all subfields of AI, as well as to demonstrate innovative applications and uses of advanced AI technology. Included here are the 158 long papers and 94 short papers selected for presentation at the conference. Many of the papers cover the fields of knowledge representation, reasoning and logic as well as agent-based and multi-agent systems, machine learning, and data mining. The proceedings of PAIS 2014 and the PAIS System Demonstrations are also included in this volume, which will be of interest to all those wishing to keep abreast of the latest developments in the field of AI.
Author: Dwivedi, Ashish N.
Publisher: IGI Global
ISBN: 1605663573
Category : Technology & Engineering
Languages : en
Pages : 1072
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Book Description
"This book presents theoretical and empirical research on the value of information technology in healthcare"--Provided by publisher.
Author: P. Morettin
Publisher: IOS Press
ISBN: 1643682679
Category : Computers
Languages : en
Pages : 112
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Book Description
Artificial intelligence often has to deal with uncertain scenarios, such as a partially observed environment or noisy observations. Traditional probabilistic models, while being very principled approaches in these contexts, are incapable of dealing with both algebraic and logical constraints. Existing hybrid continuous/discrete models are typically limited in expressivity, or do not offer any guarantee on the approximation errors. This book, Learning and Reasoning in Hybrid Structured Spaces, discusses a recent and general formalism called Weighted Model Integration (WMI), which enables probabilistic modeling and inference in hybrid structured domains. WMI-based inference algorithms differ with respect to most alternatives in that probabilities are computed inside a structured support involving both logical and algebraic relationships between variables. While the research in this area is at an early stage, we are witnessing an increasing interest in the study and development of scalable inference procedures and effective learning algorithms in this setting. This book details some of the most impactful contributions in context of WMI-based inference in the last 5 years. Moreover, by providing a gentle introduction to the main concepts related to WMI, the book can be useful for both theoretical researchers and practitioners alike.
Author: A.M. Metelli
Publisher: IOS Press
ISBN: 1643683632
Category : Computers
Languages : en
Pages : 377
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Book Description
In recent decades, Reinforcement Learning (RL) has emerged as an effective approach to address complex control tasks. In a Markov Decision Process (MDP), the framework typically used, the environment is assumed to be a fixed entity that cannot be altered externally. There are, however, several real-world scenarios in which the environment can be modified to a limited extent. This book, Exploiting Environment Configurability in Reinforcement Learning, aims to formalize and study diverse aspects of environment configuration. In a traditional MDP, the agent perceives the state of the environment and performs actions. As a consequence, the environment transitions to a new state and generates a reward signal. The goal of the agent consists of learning a policy, i.e., a prescription of actions that maximize the long-term reward. Although environment configuration arises quite often in real applications, the topic is very little explored in the literature. The contributions in the book are theoretical, algorithmic, and experimental and can be broadly subdivided into three parts. The first part introduces the novel formalism of Configurable Markov Decision Processes (Conf-MDPs) to model the configuration opportunities offered by the environment. The second part of the book focuses on the cooperative Conf-MDP setting and investigates the problem of finding an agent policy and an environment configuration that jointly optimize the long-term reward. The third part addresses two specific applications of the Conf-MDP framework: policy space identification and control frequency adaptation. The book will be of interest to all those using RL as part of their work.
