Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. First Edition (Advanced Information and Knowledge Processing) (Hardcover)

~ Asuncion Gomez-Perez (Author), Oscar Corcho (Author), Mariano Fernandez-Lopez (Author) "Ontologies are widely used in Knowledge Engineering, Artificial Intelligence and Computer Science, in applications related to knowledge management, natural language processing, e-commerce, intelligent integration information,..." (more)
Key Phrases: travel ontology, heavyweight ontologies, hoc binary relations, Ontolingua Server, Frame Ontology, American Airlines (more...)

Editorial Reviews

Product Description

Ontologies provide a common vocabulary of an area and define - with different levels of formality - the meaning of the terms and the relationships between them. Ontologies may be reused and shared across applications and groups Concepts in the ontology are usually organized in taxonomies and relations between concepts, properties of concepts, and axioms are typically used for representing the knowledge contained in ontologies. With the growth of information available, e.g. on the WWW, they are popularly applied in knowledge management, semantic web, natural language generation, enterprise modelling, knowledge-based systems, ontology-based brokers, e-commerce platforms and interoperability between systems. This book looks at questions such as: * What is an ontology? * What are the uses of ontologies? * What types of ontologies exist? What are the most well-known ones? * How do I select the best ontology for my application? * What are the principles for building an ontology? * What methodologies should I use to build my own ontology? Which techniques are appropriate for each step? * How do software tools support the process of building and using ontologies? * What language can I use to implement ontologies? * How can I integrate ontologies in a given language? The book presents the theoretical foundations of ontological engineering and covers the practical aspects of selecting and applying methodologies, tools and languages for building ontologies. The applications of ontologies are also illustrated with case studies taken from the areas of knowledge management, e-commerce and the semantic web.

From the Author

We strongly recommend this book for anyone who wants to have the most updated state of the art on Ontological Engineering, covering also the practical aspects of selecting and applying methodologies, languages, and tools for building ontologies. This book is recommended for researchers, postgraduates, practitioners, libraries, institutions, industry, scientists, students

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Product Details

• Hardcover: 415 pages
• Publisher: Springer (July 22, 2004)
• Language: English
• ISBN-10: 1852335513
• ISBN-13: 978-1852335519
• Product Dimensions: 9.1 x 6.4 x 1.3 inches
• Shipping Weight: 1.6 pounds (View shipping rates and policies)
• Average Customer Review: 3.6 out of 5 stars  See all reviews (7 customer reviews)
• Amazon.com Sales Rank: #737,976 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

21 of 24 people found the following review helpful:

4.0 out of 5 stars A good literature review of current developments, December 14, 2005

By	Dr. Lee D. Carlson (Baltimore, Maryland USA) - See all my reviews (TOP 100 REVIEWER)    (REAL NAME)

The word `ontology' is usually associated with philosophical speculation on the reality of things, and if one checks the literature on philosophy one will find a diverse number of opinions on this reality. Engineers and scientists typically view philosophical musings on any topic as being impractical, and indulging oneself in these musings will cause one to lose sight of the topic or problem at hand. Rather than simplify the problem and make it understandable, philosophy tends in most cases to complicate it by endless debate on definitions and the use of sophisticated rhetoric that seems to have no bearing on the problem at hand. The conceptual spaces generated by these debates can become gigantic and therefore unwieldy, thus making the problem appear more complex than it actually is.

In the information age however, ontology has become a word that has taken on enormous practical significance. Business and scientific research are both areas that have increasingly relied on information technology not only to organize information but also to analyze data and make accurate predictions. In addition, financial constraints have forced many businesses to automate most of their internal processes, and this automation has brought about its own unique challenges. This push to automation usually involves being able to differentiate one thing from another, or one collection of data from another, or one concept from another. Thus one needs to think about questions of ontology, and this (very practical) need has brought about the rise of the field of `ontological engineering', which is the topic of this book.

The authors have given a good general overview of the different approaches to the creation of ontologies. There are many of them, some of which seem "natural", while others seem more esoteric. The reader though will obtain an objective discussion of the ontologies that the authors chose to include in the book. Discussions of the ones that are not included can readily be found on the Internet.

Given the plethora of ontologies that have been invented, it would be of interest to the ontological engineer to find common ground between them. The re-use of a particular ontology may be stymied by the different ontological commitments it is adhering to or it's actual content. In order to use it, it must therefore be "re-engineered". The authors discuss this prospect in the book, and define `ontological re-engineering' as the process where a conceptual model of an implemented ontology is transformed into one that is more suitable. The code in which the ontology is written is first reverse engineered, and then the conceptual model is reorganized into the new one. The new conceptual model is then implemented.

Also discussed in the book, and of enormous practical interest, is the automation of the ontology building process. Called `ontology learning' by the authors, they discuss a few of the ways in which this could take place. One of these methods concerns ontology learning using a `corpus of texts', and involves being able to distinguish between the `linguistic' and `conceptual' levels. Knowledge at the linguistic level is described in linguistic terms, while at the conceptual level in terms of concepts and the relations between them. Ontology learning is thus dependent on how the linguistic structures are exemplified in the conceptual level. Relations at the conceptual level for example could be extracted from sequences of words in the text that conform to a certain pattern. Another method comes from data mining and involves the use of association rules to find relations between concepts. The authors discuss two well-known methods for ontology learning from texts. Both of these methods are interesting in that they can apparently learn in contexts or environments that are not domain-specific. Being able to learn over different domains is very important from the standpoint of the artificial intelligence community and these methods are a step in that direction. The processes of `alignment', `merging', and `cooperative construction' of ontologies that are discussed in the book are also of great interest in artificial intelligence, since they too will be of assistance in the attempt to design a machine that can reason over multiple domains.

The ontologies that are actually built are of course not unique. This results in a kind of semantic or cognitive relativism between the environments that might be built on different ontologies, even in the same domain. Merging and alignment both address this relativism, along with other techniques that are discussed in the book. The selection of the actual language that is used to create an ontology is also somewhat arbitrary. The authors devote a fair amount of space in the book to the different languages that have been used to build ontologies. Through an elementary example, they discuss eleven different languages, namely KIF, Ontolingua, LOOM, OCML, Flogic, SHOE, XOL, RDF(S), OIL, DAML+OIL, and OWL. The choice of a language is dictated by what one is seeking in terms of `expressiveness' and what kind of reasoning patterns are to be deployed when using the ontology. The authors point to a tradeoff between the expressive power of the language and the reasoning patterns that are attached to the language. The expressiveness of a language is directly proportional to the complexity of the reasoning patterns that are used.

Ontological engineering as it presently exists is still carried out by a human engineer. To create an ontology every time from scratch would be tedious, and so it is no surprise that tools were invented to make ontology creation more straightforward. Some of these tools are discussed in the book, such as KAON, OilEd, Ontolingua, OntoSaurus, Protege-2000, WebODE, and WebOnto, along with assessments as to their utility. The discussion is helpful for newcomers to ontological engineering who need guidance as to what direction to take. The automation of ontology building would of course be a major advance. To accomplish this however would require that the machine be able to simultaneously and recursively construct the knowledge base and reason over it effectively. This is a formidable challenge indeed.

11 of 12 people found the following review helpful:

4.0 out of 5 stars Very good, February 17, 2005

By	S. Nilakanta "Sree" (Ames, Iowa USA) - See all my reviews (REAL NAME)

There are several chapters that I liked and found very useful. The first chapter on theoretical foundations has been well written. Parsing through the various definitions of Ontology has been an educating experience. The other chapters, especially the ones describing the methodologies and languages are very informative. It may not be exhaustive but for a beginner, these chapters give a good overview.

I was disappointed only when I learnt that the book will not cover Ontology learning tools. The author argues for limiting the scope of the book. I feel the book would have been more valuable had it contained at least an overview of the learning tools!

7 of 8 people found the following review helpful:

4.0 out of 5 stars Good overview for beginners, April 11, 2005

By	siliconexec (San Jose, CA) - See all my reviews

The subject of this book is incredibly relevant to today's world of information management. The chapters are presented in a logical and informative way, though some of the book only skims the surface or barely touches on significant developments, tools, and problems. Overall, I found the text too theoretical, with insufficient ties to messy real-world issues.