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Ontology Learning for the Semantic Web
Ontology Learning for the Semantic Web explores techniques for applying knowledge discovery techniques to different web data sources (such as HTML documents, dictionaries, etc.), in order to support the task of engineering and maintaining ontologies. The approach of ontology learning proposed in Ontology Learning for the Semantic Web includes a number of complementary disciplines that feed in different types of unstructured and semi-structured data. This data is necessary in order to support a semi-automatic ontology engineering process. Ontology Learning for the Semantic Web is designed for researchers and developers of semantic web applications. It also serves as an excellent supplemental reference to advanced level courses in ontologies and the semantic web.
Handbook on Ontologies
An ontology is a description (like a formal specification of a program) of concepts and relationships that can exist for an agent or a community of agents. The concept is important for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies. The handbook demonstrates standards that have been created recently, it surveys methods that have been developed and it shows how to bring both into practice of ontology infrastructures and applications that are the best of their kind.
The Semantic Web: Research and Applications
This volume contains the papers presented at the 2nd European Semantic Web Conference (ESWC 2005) held in Heraklion, Crete, Greece, from 29th May to 1st June, 2005. The vision of the Semantic Web is to enhance today’s Web via the exploi- tion of machine-processable metadata. The explicit representation of the sem- tics of data, accompanied with domain theories (ontologies), will enable a web that provides a qualitatively new level of service. It will weave together an - crediblylargenetworkofhumanknowledgeandwillcomplementitwithmachine processability. Various automated services will help the user to achieve goals by accessing and providing information in a machine-understandable form. This...
Perspectives on Ontology Learning
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.
Collaborative Business Ecosystems and Virtual Enterprises
Towards collaborative business ecosystems Last decade was fertile in the emerging of new collaboration mechanisms and forms of dynamic virtual organizations, leading to the concept of dynamic business ecosystem, which is supported (or induced ?) by the progress of the ubiquitous I pervasive computing and networking. The new technologies, collaborative business models, and organizational forms supported by networking tools "invade" all traditional businesses and organizations what requires thinking in terms of whole systems, i. e. seeing each business as part of a wider economic ecosystem and environment. It is also becoming evident that the agile formation of very dynamic virtual organizatio...
Information Systems and Neuroscience
This book presents the proceedings of the Gmunden Retreat on NeuroIS 2017, reporting on topics at the intersection of Information Systems (IS) research, neurophysiology and the brain sciences. Readers will discover the latest findings from top scholars in the field of NeuroIS, which offer detailed insights on the neurobiology underlying IS behavior, essential methods and tools and their applications for IS, as well as the application of neuroscience and neurophysiological theories to advance IS theory.
Spinning the Semantic Web
A guide to the Semantic Web, which will transform the Web into a structured network of resources organized by meaning and relationships.
Natural Language Processing and Information Systems
This book includes the papers presented at the fifth International Conference on Application of Natural Language to Information Systems (NLDB 2000) which was held in Versailles (France) on June 28-30. Following NLDB95 in Versailles, NLDB96 i n Amsterdam, NLDB97 i n Vancouver, and NLDB99 i n Klagenfurt, NLDB 2000 was a forum for exchanging new research results and trends on the benefits of integrating Natural Language resources in Information System Engineering. Since the first NLDB workshop in 1995 it has become apparent that each aspect of an information system life cycle may be improved by natural language techniques: database design (specification, validation, conflict resolution), databa...
Design Science Research. Cases
Design Science Research is a powerful paradigm enabling researchers to make important contributions to society and industry. Simply stated, the goal of DSR is to generate knowledge on how to find innovative solutions to important problems in the form of models, methods, constructs and instantiations. Over the past 20 years, the design science research (DSR) paradigm has developed into an established paradigm in Information Systems Research and it is of strong uptake in many other disciplines, including Management Science and Computer Science. This book provides a collection of twelve DSR cases, presented by experienced researchers in the field. It offers readers access to real-world DSR studies, together with the authors’ reflections on their research processes. These cases will support researchers who want to engage in DSR, and represent a valuable addition to existing introductions to DSR methods and processes. Readers will learn from the hands-on experiences of respected experts who have conducted extensive DSR in a range of application contexts.
Knowledge Engineering and Knowledge Management. Methods, Models, and Tools
This book constitutes the refereed proceedings of the 12th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2000, held in Juan-les-Pins, France in October 2000. The 28 revised full papers and six revised short papers presented were carefully reviewed and selected from a high number of high-quality submissions. The book offers topical sections on knowledge modeling languages and tools, ontologies, knowledge acquisition from texts, machine learning, knowledge management and electronic commerce, problem solving methods, knowledge representation, validation, evaluation and certification, and methodologies.
