Knowledge Management and Knowledge Engineering is a fascinating ?eld of re- 1 search these days. In the beginning of EKAW , the modeling and acquisition of knowledge was the privilege of – or rather a burden for – a few knowledge engineers familiar with knowledge engineering paradigms and knowledge rep- sentationformalisms.While the aimhasalwaysbeentomodelknowledgedecl- atively and allow for reusability, the knowledge models produced in these early days were typically used in single and very speci?c applications and rarely - changed. Moreover, these models were typically rather complex, and they could be understood only by a few expert knowledge engineers. This situation has changed radically in the last few years as clearly indicated by the following trends: – The creation of (even formal) knowledge is now becoming more and more collaborative. Collaborative ontology engineering tools and social software platforms show the potential to leverage the wisdom of the crowds (or at least of “the many”) to lead to broader consensus and thus produce shared models which qualify better for reuse. – A trend can also be observed towards developing and publishing small but 2 3 4 high-impactvocabularies(e.g.,FOAF ,DublinCore ,GoodRelations)rather than complex and large knowledge models.
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Knowledge Management and Knowledge Engineering is a fascinating ?eld of re- 1 search these days. In the beginning of EKAW , the modeling and acquisition of knowledge was the privilege of – or rather a burden for – a few knowledge engineers familiar with knowledge engineering paradigms and knowledge rep- sentationformalisms.While the aimhasalwaysbeentomodelknowledgedecl- atively and allow for reusability, the knowledge models produced in these early days were typically used in single and very speci?c applications and rarely - changed. Moreover, these models were typically rather complex, and they could be understood only by a few expert knowledge engineers. This situation has changed radically in the last few years as clearly indicated by the following trends: – The creation of (even formal) knowledge is now becoming more and more collaborative. Collaborative ontology engineering tools and social software platforms show the potential to leverage the wisdom of the crowds (or at least of “the many”) to lead to broader consensus and thus produce shared models which qualify better for reuse. – A trend can also be observed towards developing and publishing small but 2 3 4 high-impactvocabularies(e.g.,FOAF ,DublinCore ,GoodRelations)rather than complex and large knowledge models.
This book constitutes the refereed proceedings of the 17th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2010, held in Lisbon, Portugal, in October 2010. The 22 revised full papers and 25 revised short papers presented were carefully reviewed and selected from 166 submissions. The papers are organized in topical sections on knowledge engineering: alignment and identity, knowledge acquisition collaboration in knowledge engineering knowledge engineering: patterns social aspects and tagging semantic web, web of data and linked data ontology evolution and refinement knowledge access annotation, retrieval and natural language processing.
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Taschenbuch. Zustand: Neu. Neuware - Knowledge Management and Knowledge Engineering is a fascinating eld of re- 1 search these days. In the beginning of EKAW , the modeling and acquisition of knowledge was the privilege of - or rather a burden for - a few knowledge engineers familiar with knowledge engineering paradigms and knowledge rep- sentationformalisms.While the aimhasalwaysbeentomodelknowledgedecl- atively and allow for reusability, the knowledge models produced in these early days were typically used in single and very speci c applications and rarely - changed. Moreover, these models were typically rather complex, and they could be understood only by a few expert knowledge engineers. This situation has changed radically in the last few years as clearly indicated by the following trends: - The creation of (even formal) knowledge is now becoming more and more collaborative. Collaborative ontology engineering tools and social software platforms show the potential to leverage the wisdom of the crowds (or at least of 'the many') to lead to broader consensus and thus produce shared models which qualify better for reuse. - A trend can also be observed towards developing and publishing small but 2 3 4 high-impactvocabularies(e.g.,FOAF ,DublinCore ,GoodRelations)rather than complex and large knowledge models. Artikel-Nr. 9783642164378
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