Building and Evaluating Domain Ontologies

Building and Evaluating Domain Ontologies
Author: Gintarė Grigonytė
Publisher: Logos Verlag Berlin GmbH
Total Pages: 213
Release: 2010
Genre: Computers
ISBN: 3832526579

An ontology is a knowledge representation structure made up of concepts and their interrelations. It represents shared understanding delineated by some domain. The building of an ontology can be addressed from the perspective of natural language processing. This thesis discusses the validity and theoretical background of knowledge acquisition from natural language. It also presents the theoretical and experimental framework for NLP-driven ontology building and evaluation tasks.

Ontology Learning from Text

Ontology Learning from Text
Author: Paul Buitelaar
Publisher: IOS Press
Total Pages: 188
Release: 2005
Genre: Computers
ISBN: 9781586035235

The latest title in Black Library's premium line. Perturabo - master of siegecraft, and executioner of Olympia. Long has he lived in the shadow of his more favoured primarch brothers, frustrated by the mundane and ignominious duties which regularly fall to his Legion. When Fulgrim offers him the chance to lead an expedition in search of an ancient and destructive xenos weapon, the Iron Warriors and the Emperor's Children unite and venture deep into the heart of the great warp-rift known only as 'the Eye'. Pursued by a ragged band of survivors from Isstvan V and the revenants of a dead eldar world, they must work quickly if they are to unleash the devastating power of the Angel Exterminatus

Ontological Engineering approach of developing Ontology of Information Science

Ontological Engineering approach of developing Ontology of Information Science
Author: Ahlam F. Sawsaa
Publisher: Anchor Academic Publishing
Total Pages: 297
Release: 2015-06-25
Genre: Computers
ISBN: 3954899485

Ontology has been a subject of many studies carried out in artificial intelligence (AI) and information system communities. Ontology has become an important component of the semantic web, covering a variety of knowledge domains. Although building domain ontologies still remains a big challenge with regard to its designing and implementation, there are still many areas that need to create ontologies. Information Science (IS) is one of these areas that need a unified ontology model to facilitate information access among the heterogeneous data resources and share a common understanding of the domain knowledge. Recently, the development of domain ontologies has become increasingly important for knowledge level interoperation and information integration. They provide functional features for AI and knowledge representation. Domain Ontology is a central foundation of growth for the semantic web that provides a general knowledge for correspondence and communication among heterogeneous systems. Particularly with a rise of ontology in the artificial intelligence (AI) domain, it can be seen as an almost inevitable development in computer science and AI in general.

Ontological Engineering

Ontological Engineering
Author: Asunción Gómez-Pérez
Publisher: Springer Science & Business Media
Total Pages: 412
Release: 2006-04-18
Genre: Computers
ISBN: 1852338407

Ontological Engineering refers to the set of activities that concern the ontology development process, the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. During the last decade, increasing attention has been focused on ontologies and Ontological Engineering. Ontologies are now widely used in Knowledge Engineering, Artificial Intelligence and Computer Science; in applications related to knowledge management, natural language processing, e-commerce, intelligent integration information, information retrieval, integration of databases, b- informatics, and education; and in new emerging fields like the Semantic Web. Primary goals of this book are to acquaint students, researchers and developers of information systems with the basic concepts and major issues of Ontological Engineering, as well as to make ontologies more understandable to those computer science engineers that integrate ontologies into their information systems. We have paid special attention to the influence that ontologies have on the Semantic Web. Pointers to the Semantic Web appear in all the chapters, but specially in the chapter on ontology languages and tools.

A Generic Model of Ontology to Visualize Information Science Domain (OIS).

A Generic Model of Ontology to Visualize Information Science Domain (OIS).
Author: Ahlam Sawsaa
Publisher:
Total Pages:
Release: 2013
Genre:
ISBN:

Ontology has been a subject of many studies carried out in artificial intelligence (AI) and information system communities. Ontology has become an important component of the semantic web, covering a variety of knowledge domains. Although building domain ontologies still remains a big challenge with regard to its designing and implementation, there are still many areas that need to create ontologies. Information Science (IS) is one of these areas that need a unified ontology model to facilitate information access among the heterogeneous data resources and share a common understanding of the domain knowledge. The objective of this study is to develop a generic model of ontology that serves as a foundation of knowledge modelling for applications and aggregation with other ontologies to facilitate information exchanging between different systems. This model will be a metadata for a knowledge base system to be used in different purposes of interest, such as education applications to support educational needs for teachers and students and information system developers, and enhancing the index tool in libraries to facilitate access to information collections. This thesis describes the process of modelling the domain knowledge of Information Science IS. The building process of the ontology of Information Science (OIS) is preceded by developing taxonomies and thesauruses of IS. This research adopts the Methontology to develop ontology of Information Science OIS. This choice of method relies on the research motivations and aims, with analysis of some development ontology methodologies and IEEE 1074-2006 standards for developing software project life cycle processes as criteria. The methodology mainly consisted of; specification, conceptualization, formalization, implementation, maintenance and evaluation. The knowledge model was formalized using Protégé to generate the ontology code. During the development process the model has been designed and evaluated. This research presents the following contributions to the present state of the art on ontology construction; - The main achievement of the study is in constructing a new model of Information Science ontology OIS. The OIS ontology is a generic model that contains only the key objects and associated attributes with relationships. The model has defined 706 concepts which will be widely used in Information Science applications. It provides the standard definitions for domain terms used in annotation databases for the domain terms, and avoids the consistency problems caused by various ontologies which will have the potential of development by different groups and institutions in the IS domain area. - It provides a framework for analyzing the IS knowledge to obtain a classification based on facet classification. The ontology modelling approach is based on topdown and bottom-up. The top-down begins with an abstract of the domain view. While the bottom-up method starts with description of the domain to gain a hierarchal taxonomy. - Designing Ontocop system a novel method presented to support the developing process as specific virtual community of IS. The Ontocop consists of a number of experts in the subject area around the world. Their feedback and assessment improve the ontology development during the creating process. The findings of the research revealed that overall feedback from the IS community has been positive and that the model met the ontology quality criteria. It was appropriate to provide consistency and clear understanding of the subject area. OIS ontology unifies information science, which is composed of library science, computer science and archival science, by creating the theoretical base useful for further practical systems. Developing ontology of information science (OIS) is not an easy task, due to the complex nature of the field. It needs to be integrated with other ontologies such as social science, cognitive science, philosophy, law management and mathematics, to provide a basic knowledge for the semantic web and also to leverage information retrieval.

Building Ontologies with Basic Formal Ontology

Building Ontologies with Basic Formal Ontology
Author: Robert Arp
Publisher: MIT Press
Total Pages: 245
Release: 2015-08-28
Genre: Science
ISBN: 026232959X

An introduction to the field of applied ontology with examples derived particularly from biomedicine, covering theoretical components, design practices, and practical applications. In the era of “big data,” science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of particular relevance to biomedicine, covering theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use. After defining an ontology as a representation of the types of entities in a given domain, the book distinguishes between different kinds of ontologies and taxonomies, and shows how applied ontology draws on more traditional ideas from metaphysics. It presents the core features of the Basic Formal Ontology (BFO), now used by over one hundred ontology projects around the world, and offers examples of domain ontologies that utilize BFO. The book also describes Web Ontology Language (OWL), a common framework for Semantic Web technologies. Throughout, the book provides concrete recommendations for the design and construction of domain ontologies.

Ontology Learning and Population

Ontology Learning and Population
Author: Paul Buitelaar
Publisher: IOS Press
Total Pages: 292
Release: 2008
Genre: Computers
ISBN: 1586038184

The promise of the Semantic Web is that future web pages will be annotated not only with bright colors and fancy fonts as they are now, but with annotation extracted from large domain ontologies that specify, to a computer in a way that it can exploit, what information is contained on the given web page. The presence of this information will allow software agents to examine pages and to make decisions about content as humans are able to do now. The classic method of building an ontology is to gather a committee of experts in the domain to be modeled by the ontology, and to have this committee.

Knowledge Management in Construction

Knowledge Management in Construction
Author: Chimay J. Anumba
Publisher: John Wiley & Sons
Total Pages: 243
Release: 2008-04-15
Genre: Technology & Engineering
ISBN: 0470759526

A key problem facing the construction industry is that all work is done by transient project teams, and in the past there has been no structured approach to learning from projects once they are completed. Now, though, the industry is adapting concepts of knowledge management to improve the situation. This book brings together 13 contributors from research and industry to show how managing construction knowledge can bring real benefits to organisations and projects. It covers a wide range of issues, from basic definitions and fundamental concepts, to the role of information technology, and engendering a knowledge sharing culture. Practical examples from construction and other industry sectors are used throughout to illustrate the various dimensions of knowledge management. The challenges of implementing knowledge management are outlined and the ensuing benefits highlighted.

Next Generation Intelligent Environments

Next Generation Intelligent Environments
Author: Stefan Ultes
Publisher: Springer
Total Pages: 364
Release: 2015-11-30
Genre: Technology & Engineering
ISBN: 3319234528

This book covers key topics in the field of intelligent ambient adaptive systems. It focuses on the results worked out within the framework of the ATRACO (Adaptive and TRusted Ambient eCOlogies) project. The theoretical background, the developed prototypes, and the evaluated results form a fertile ground useful for the broad intelligent environments scientific community as well as for industrial interest groups. The new edition provides: Chapter authors comment on their work on ATRACO with final remarks as viewed in retrospective Each chapter has been updated with follow-up work emerging from ATRACO An extensive introduction to state-of-the-art statistical dialog management for intelligent environments Approaches are introduced on how Trust is reflected during the dialog with the system