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Ontology Learning and Population

Ontology Learning and Population PDF Author: Paul Buitelaar
Publisher: IOS Press
ISBN: 1586038184
Category : Computers
Languages : en
Pages : 292

Book Description
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.

Ontology Learning and Population

Ontology Learning and Population PDF Author: Paul Buitelaar
Publisher: IOS Press
ISBN: 1586038184
Category : Computers
Languages : en
Pages : 292

Book Description
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.

Ontology Learning and Population

Ontology Learning and Population PDF Author: Paul Buitelaar
Publisher:
ISBN: 9781433711305
Category : Artificial intelligence
Languages : en
Pages : 273

Book Description


Ontology Learning and Population: Bridging the Gap Between Text and Knowledge

Ontology Learning and Population: Bridging the Gap Between Text and Knowledge PDF Author: P. Buitelaar
Publisher: IOS Press
ISBN: 1607502968
Category : Computers
Languages : en
Pages : 292

Book Description
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 agree on which concepts cover the domain, on which terms describe which concepts, on what relations exist between each concept and what the possible attributes of each concept are. All ontology learning systems begin with an ontology structure, which may just be an empty logical structure, and a collection of texts in the domain to be modeled. An ontology learning system can be seen as an interplay between three things: an existing ontology, a collection of texts, and lexical syntactic patterns. The Semantic Web will only be a reality if we can create structured, unambiguous ontologies that model domain knowledge that computers can handle. The creation of vast arrays of such ontologies, to be used to mark-up web pages for the Semantic Web, can only be accomplished by computer tools that can extract and build large parts of these ontologies automatically. This book provides the state-of-art of many automatic extraction and modeling techniques for ontology building. The maturation of these techniques will lead to the creation of the Semantic Web.

Knowledge-Driven Multimedia Information Extraction and Ontology Evolution

Knowledge-Driven Multimedia Information Extraction and Ontology Evolution PDF Author: Georgios Paliouras
Publisher: Springer Science & Business Media
ISBN: 3642207944
Category : Computers
Languages : en
Pages : 251

Book Description
This book presents the state of the art in the areas of ontology evolution and knowledge-driven multimedia information extraction, placing an emphasis on how the two can be combined to bridge the semantic gap. This was also the goal of the EC-sponsored BOEMIE (Bootstrapping Ontology Evolution with Multimedia Information Extraction) project, to which the authors of this book have all contributed. The book addresses researchers and practitioners in the field of computer science and more specifically in knowledge representation and management, ontology evolution, and information extraction from multimedia data. It may also constitute an excellent guide to students attending courses within a computer science study program, addressing information processing and extraction from any type of media (text, images, and video). Among other things, the book gives concrete examples of how several of the methods discussed can be applied to athletics (track and field) events.

Uncertainty Reasoning for the Semantic Web II

Uncertainty Reasoning for the Semantic Web II PDF Author: Fernando Bobillo
Publisher: Springer
ISBN: 3642359752
Category : Computers
Languages : en
Pages : 331

Book Description
This book contains revised and significantly extended versions of selected papers from three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conferences (ISWC) in 2008, 2009, and 2010 or presented at the first international Workshop on Uncertainty in Description Logics (UniDL), held at the Federated Logic Conference (FLoC) in 2010. The 17 papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on probabilistic and Dempster-Shafer models, fuzzy and possibilistic models, inductive reasoning and machine learning, and hybrid approaches.

 PDF Author:
Publisher: IOS Press
ISBN:
Category :
Languages : en
Pages : 4947

Book Description


Ontology Learning and Population from Text

Ontology Learning and Population from Text PDF Author: Philipp Cimiano
Publisher: Springer Science & Business Media
ISBN: 0387392521
Category : Computers
Languages : en
Pages : 362

Book Description
In the last decade, ontologies have received much attention within computer science and related disciplines, most often as the semantic web. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications discusses ontologies for the semantic web, as well as knowledge management, information retrieval, text clustering and classification, as well as natural language processing. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications is structured for research scientists and practitioners in industry. This book is also suitable for graduate-level students in computer science.

Universal Access in Human-Computer Interaction. Design for All and eInclusion

Universal Access in Human-Computer Interaction. Design for All and eInclusion PDF Author: Constantine Stephanidis
Publisher: Springer
ISBN: 3642216722
Category : Computers
Languages : en
Pages : 534

Book Description
The four-volume set LNCS 6765-6768 constitutes the refereed proceedings of the 6th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2011, held as Part of HCI International 2011, in Orlando, FL, USA, in July 2011, jointly with 10 other conferences addressing the latest research and development efforts and highlighting the human aspects of design and use of computing systems. The 57 revised papers included in the first volume were carefully reviewed and selected from numerous submissions. The papers are organized in the following topical sections: design for all methods and tools; Web accessibility: approaches, methods and tools; multimodality, adaptation and personlization; and eInclusion policy, good practice, legislation and security issues.

Perspectives on Ontology Learning

Perspectives on Ontology Learning PDF Author: J. Lehmann
Publisher: IOS Press
ISBN: 1614993793
Category : Computers
Languages : en
Pages : 299

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.

Uncertainty Reasoning for the Semantic Web I

Uncertainty Reasoning for the Semantic Web I PDF Author: Paulo C. G. Costa
Publisher: Springer Science & Business Media
ISBN: 354089764X
Category : Computers
Languages : en
Pages : 416

Book Description
This book constitutes the thoroughly refereed first three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conferences (ISWC) in 2005, 2006, and 2007. The 22 papers presented are revised and strongly extended versions of selected workshops papers as well as invited contributions from leading experts in the field and closely related areas. The present volume represents the first comprehensive compilation of state-of-the-art research approaches to uncertainty reasoning in the context of the semantic Web, capturing different models of uncertainty and approaches to deductive as well as inductive reasoning with uncertain formal knowledge.