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Author: V.A. Carriero
Publisher: IOS Press
ISBN: 1643684795
Category : Computers
Languages : en
Pages : 154
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Book Description
In recent years, knowledge graphs (KGs) and ontologies have been widely adopted for modeling many kinds of domain. They are frequently released openly, something which benefits those who are starting new projects, because it offers them a wide choice of ontology reuse and the possibility to link to existing data. Understanding the content of an ontology or a knowledge graph is far from straightforward, however, and existing methods address this issue only partially, while exploring and comparing multiple ontologies can be a tedious manual task. This book, Empirical Ontology Design Patterns, starts from the premise that identifying the Ontology Design Patterns (ODPs) used in an ontology or a knowledge graph will go some way to addressing this problem. Its main focus is to provide tools which will effectively support the task of automatically identifying ODPs in existing ontologies and knowledge graphs. The book analyses the role of ODPs in ontology engineering, placing this analysis in the wider context of existing approaches to ontology reuse and implementation. It introduces a novel method for extracting empirical ontology design patterns (EODPs) from ontologies, and another for extracting EODPs from knowledge graphs whose schemas are implicit. Both methods are applied to ontologies and knowledge graphs frequently adopted and reused, such as Wikidata. The book also offers an ontology which can be used as a basis for annotating ODPs in ontologies and knowledge graphs, whether manually or automatically. The book will be of interest to all those whose work involves the use or reuse of ontologies and knowledge graphs.
Author: V.A. Carriero
Publisher: IOS Press
ISBN: 1643684795
Category : Computers
Languages : en
Pages : 154
Get Book
Book Description
In recent years, knowledge graphs (KGs) and ontologies have been widely adopted for modeling many kinds of domain. They are frequently released openly, something which benefits those who are starting new projects, because it offers them a wide choice of ontology reuse and the possibility to link to existing data. Understanding the content of an ontology or a knowledge graph is far from straightforward, however, and existing methods address this issue only partially, while exploring and comparing multiple ontologies can be a tedious manual task. This book, Empirical Ontology Design Patterns, starts from the premise that identifying the Ontology Design Patterns (ODPs) used in an ontology or a knowledge graph will go some way to addressing this problem. Its main focus is to provide tools which will effectively support the task of automatically identifying ODPs in existing ontologies and knowledge graphs. The book analyses the role of ODPs in ontology engineering, placing this analysis in the wider context of existing approaches to ontology reuse and implementation. It introduces a novel method for extracting empirical ontology design patterns (EODPs) from ontologies, and another for extracting EODPs from knowledge graphs whose schemas are implicit. Both methods are applied to ontologies and knowledge graphs frequently adopted and reused, such as Wikidata. The book also offers an ontology which can be used as a basis for annotating ODPs in ontologies and knowledge graphs, whether manually or automatically. The book will be of interest to all those whose work involves the use or reuse of ontologies and knowledge graphs.
Author: P. Hitzler
Publisher: IOS Press
ISBN: 1614996768
Category : Computers
Languages : en
Pages : 388
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Book Description
The use of ontologies for data and knowledge organization has become ubiquitous in many data-intensive and knowledge-driven application areas, in science, industry, and the humanities. At the same time, ontology engineering best practices continue to evolve. In particular, modular ontology modeling based on ontology design patterns is establishing itself as an approach for creating versatile and extendable ontologies for data management and integration. This book is the very first comprehensive treatment of Ontology Engineering with Ontology Design Patterns. It contains both advanced and introductory material accessible for readers with only a minimal background in ontology modeling. Some introductory material is written in the style of tutorials, and specific chapters are devoted to examples and to applications. Other chapters convey the state of the art in research regarding ontology design patterns. The editors and the contributing authors include the leading contributors to the development of ontology-design-pattern-driven ontology engineering.
Author: K. Hammar
Publisher: IOS Press
ISBN: 1614998264
Category : Computers
Languages : en
Pages : 162
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Book Description
The study of patterns in the context of ontology engineering for the semantic web was pioneered more than a decade ago by Blomqvist, Sandkuhl and Gangemi. Since then, this line of research has flourished and led to the development of ontology design patterns, knowledge patterns, and linked data patterns: the patterns as they are known by ontology designers, knowledge engineers, and linked data publishers, respectively. A key characteristic of those patterns is that they are modular and reusable solutions to recurrent problems in ontology engineering and linked data publishing. This book contains recent contributions which advance the state of the art on theory and use of ontology design patterns. The papers collected in this book cover a range of topics, from a method to instantiate content patterns, a proposal on how to document a content pattern, to a number of patterns emerging in ontology modeling in various situations.
Author: E. Blomqvist
Publisher: IOS Press
ISBN: 1643681753
Category : Computers
Languages : en
Pages : 406
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Book Description
Ontologies are the corner stone of data modeling and knowledge representation, and engineering an ontology is a complex task in which domain knowledge, ontological accuracy and computational properties need to be carefully balanced. As with any engineering task, the identification and documentation of common patterns is important, and Ontology Design Patterns (ODPs) provide ontology designers with a strong connection to requirements and a better communication of their semantic content and intent. This book, Advances in Pattern-Based Ontology Engineering, contains 23 extended versions of selected papers presented at the annual Workshop on Ontology Design and Patterns (WOP) between 2017 and 2020. This yearly event, which attracts a large number of researchers and professionals in the field of ontology engineering and ontology design patterns, covers issues related to quality aspects of ontology engineering and ODPs for data and knowledge representation, and is usually co-located with the International Semantic Web Conference (ISWC), apart from WOP 2020, which was held virtually due to the COVID-19 pandemic. Topics covered by the papers collected here focus on recent advances in ontology design and patterns, and range from a method to instantiate content patterns, through a proposal on how to document a content pattern, to a number of patterns emerging in ontology modeling in various situations and applications. The book provides an overview of important advances in ontology engineering and ontology design patterns, and will be of interest to all those working in the field.
Author: J. Lehmann
Publisher: IOS Press
ISBN: 1614993793
Category : Computers
Languages : en
Pages : 299
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Book Description
Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning. Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the creation of simple taxonomical structures, as well as on problems specifically related to knowledge modeling and representation using the Web Ontology Language. Perspectives on Ontology Learning is designed for researchers in the field of semantic technologies and developers of knowledge-based applications. It covers various aspects of ontology learning including ontology quality, user interaction, scalability, knowledge acquisition from heterogeneous sources, as well as the integration with ontology engineering methodologies.
Author: Karl Hammar
Publisher: Linköping University Electronic Press
ISBN: 917685454X
Category :
Languages : en
Pages : 238
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Book Description
Ontologies are formal knowledge models that describe concepts and relationships and enable data integration, information search, and reasoning. Ontology Design Patterns (ODPs) are reusable solutions intended to simplify ontology development and support the use of semantic technologies by ontology engineers. ODPs document and package good modelling practices for reuse, ideally enabling inexperienced ontologists to construct high-quality ontologies. Although ODPs are already used for development, there are still remaining challenges that have not been addressed in the literature. These research gaps include a lack of knowledge about (1) which ODP features are important for ontology engineering, (2) less experienced developers' preferences and barriers for employing ODP tooling, and (3) the suitability of the eXtreme Design (XD) ODP usage methodology in non-academic contexts. This dissertation aims to close these gaps by combining quantitative and qualitative methods, primarily based on five ontology engineering projects involving inexperienced ontologists. A series of ontology engineering workshops and surveys provided data about developer preferences regarding ODP features, ODP usage methodology, and ODP tooling needs. Other data sources are ontologies and ODPs published on the web, which have been studied in detail. To evaluate tooling improvements, experimental approaches provide data from comparison of new tools and techniques against established alternatives. The analysis of the gathered data resulted in a set of measurable quality indicators that cover aspects of ODP documentation, formal representation or axiomatisation, and usage by ontologists. These indicators highlight quality trade-offs: for instance, between ODP Learnability and Reusability, or between Functional Suitability and Performance Efficiency. Furthermore, the results demonstrate a need for ODP tools that support three novel property specialisation strategies, and highlight the preference of inexperienced developers for template-based ODP instantiation---neither of which are supported in prior tooling. The studies also resulted in improvements to ODP search engines based on ODP-specific attributes. Finally, the analysis shows that XD should include guidance for the developer roles and responsibilities in ontology engineering projects, suggestions on how to reuse existing ontology resources, and approaches for adapting XD to project-specific contexts.
Author: A. Ławrynowicz
Publisher: IOS Press
ISBN: 1614997462
Category : Computers
Languages : en
Pages : 210
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Book Description
Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining – a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data. The introductory chapters of the book provide theoretical foundations of both data mining and ontology representation. Taking a unified perspective, the book then covers several methods for semantic data mining, addressing tasks such as pattern mining, classification and similarity-based approaches. It attempts to provide state-of-the-art answers to specific challenges and peculiarities of data mining with use of ontologies, in particular: How to deal with incompleteness of knowledge and the so-called Open World Assumption? What is a truly “semantic” similarity measure? The book contains several chapters with examples of applications of semantic data mining. The examples start from a scenario with moderate use of lightweight ontologies for knowledge graph enrichment and end with a full-fledged scenario of an intelligent knowledge discovery assistant using complex domain ontologies for meta-mining, i.e., an ontology-based meta-learning approach to full data mining processes. The book is intended for researchers in the fields of semantic technologies, knowledge engineering, data science, and data mining, and developers of knowledge-based systems and applications.
Author: Chiara Ghidini
Publisher: Springer Nature
ISBN: 303030793X
Category : Computers
Languages : en
Pages : 754
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Book Description
The two-volume set of LNCS 11778 and 11779 constitutes the refereed proceedings of the 18th International Semantic Web Conference, ISWC 2019, held in Auckland, New Zealand, in October 2019. The ISWC conference is the premier international forum for the Semantic Web / Linked Data Community. The total of 74 full papers included in this volume was selected from 283 submissions. The conference is organized in three tracks: for the Research Track 42 full papers were selected from 194 submissions; the Resource Track contains 21 full papers, selected from 64 submissions; and the In-Use Track features 11 full papers which were selected from 25 submissions to this track.
Author: P. Ristoski
Publisher: IOS Press
ISBN: 1614999813
Category : Computers
Languages : en
Pages : 246
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Book Description
Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process. This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation strategies from types and relations in knowledge graphs used in different data mining tasks such as classification, regression, and outlier detection. Part II, Semantic Web Knowledge Graphs Embeddings, proposes an approach that circumvents the shortcomings introduced with the approaches in Part I, developing an approach that is able to embed complete Semantic Web knowledge graphs in a low dimensional feature space where each entity and relation in the knowledge graph is represented as a numerical vector. Finally, Part III, Applications of Semantic Web Knowledge Graphs, describes a list of applications that exploit Semantic Web knowledge graphs like classification and regression, showing that the approaches developed in Part I and Part II can be used in applications in various domains. The book will be of interest to all those working in the field of data mining and KDD.
Author: Jeffrey T. Pollock
Publisher: John Wiley & Sons
ISBN: 0471714208
Category : Technology & Engineering
Languages : en
Pages : 440
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Book Description
New Paradigm for considering application integration and B2Bproblems Heightens the importance of conveying meaning betweensystems Addresses movement in the EAI space toward more data handlingcapabilities Offers a solution for the multitude of managers disconnectedwith the latest technologies Leverages the technical advances made in complex dataintegration over 15 years Shifts the focus from technology solutions to informationsolutions Relies heavily on the use of practical examples, tips,definitions, and soapbox excerpts throughout the main body oftext
