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Information infrastructures are integrated solutions based on the fusion of information and communication technologies. They are characterized by the large amount of data that must be managed accordingly. An information infrastructure requires an efficient and effective information retrieval system to provide access to the items stored in the infrastructure. Terminological Ontologies: Design, Management and Practical Applications presents the main problems that affect the discovery systems of information infrastructures to manage terminological models, and introduces a combination of research tools and applications in Semantic Web technologies. This book specifically analyzes the need to create, relate, and integrate the models required for an infrastructure by elaborating on the problem of accessing these models in an efficient manner via interoperable services and components.

Terminological Ontologies: Design, Management and Practical Applications is geared toward information management systems and semantic web professionals working as project managers, application developers, government workers and more. Advanced undergraduate and graduate level students, professors and researchers focusing on computer science will also find this book valuable as a secondary text or reference book.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Ontology basic concepts

Abstract
According to Gruber [69], an ontology is an explicit specification of a conceptualization. A conceptualization is an abstract, simplified view of the world that we wish to represent for some purpose. A body of formally represented knowledge is based on a conceptualization: the objects, concepts, and other entities that are presumed to exist in some area of interest and the relationships that hold between them. Every knowledge base, knowledge-based system, or knowledge-level agent is committed to some conceptualization, explicitly or implicitly.
Javier Lacasta, Javier Nogueras-Iso, Francisco Javier Zarazaga-Soria

Chapter 2. A representation framework for terminological ontologies

Abstract
From the different types of ontology models, terminological ontologies are intensively used by libraries, archives, museums and any other registry of information to facilitate the location of stored resources (classification and information retrieval). Historically, terminological models were printed and used as thematic indexes to locate associated resources. The development of new applications have translated them into the computers and made them to evolve quickly. They are domain or application models that contain the terminology required in an area of knowledge for a specific application and along the years, they have proven to be a useful tool to deal with ambiguity problems, providing inter-relation structure and semantics to the terminology used in these systems. Nowadays, there is a great deal of terminological models covering every area of interest and they have become a crucial part of the information retrieval systems of digital libraries, catalogues and any other system where information is searched or presented thematically.
Javier Lacasta, Javier Nogueras-Iso, Francisco Javier Zarazaga-Soria

Chapter 3. Ontology learning for terminological ontologies

Abstract
The use of suitable terminological ontologies is vital in classification and information retrieval to obtain high quality results. For example, in a discovery system, if the resources are annotated using a vocabulary that does not contain all the required terms to describe the collection, the construction of an effective search system becomes much more difficult.
Javier Lacasta, Javier Nogueras-Iso, Francisco Javier Zarazaga-Soria

Chapter 4. Formalization of terminological ontologies

Abstract
The applicability of thesauri in the classification and information retrieval context has promoted the creation and diffusion of well-established thesauri in many different domains. These simple models are useful for most of classification and retrieval systems where search requisites are not very elaborated; however, in contexts with an information model of great complexity, more elaborated ontologies with formal is-a hierarchies, frame definitions or even general logical constraints are needed to improve the retrieval quality.
Javier Lacasta, Javier Nogueras-Iso, Francisco Javier Zarazaga-Soria

Chapter 5. Access to terminological ontologies

Abstract
Typical information infrastructures manage different terminological ontologies with a very different levels of specificity, language coverage integrated in their systems (e.g., from monolingual lists of terms to multilingual thesauri covering more than 20 languages), formalization, (e.g., from simple glossaries to well-structured thesauri), or size, (e.g., AGROVOC thesaurus [126] contains more than 16,000 concepts).
Javier Lacasta, Javier Nogueras-Iso, Francisco Javier Zarazaga-Soria

Chapter 6. Applicability of terminological ontologies to information retrieval

Abstract
The previous chapters have focused on describing different strategies, processes, components and systems to improve the management of terminological ontologies. This chapter takes all those elements and applies them to improve information discovery and retrieval in an information infrastructure.
Javier Lacasta, Javier Nogueras-Iso, Francisco Javier Zarazaga-Soria

Chapter 7. Concluding remarks and outlook

Abstract
In any information infrastructure, the information retrieval components have a special relevance because they are the components that provide the first point of access to the contents. Improving these components involves an improvement in the entire infrastructure environment, making the resource holdings easier to find and access.
Javier Lacasta, Javier Nogueras-Iso, Francisco Javier Zarazaga-Soria

Backmatter

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