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Knowledge Engineering: Practice and Patterns

17th International Conference, EKAW 2010, Lisbon, Portugal, October 11-15, 2010, Proceedings

  • Conference proceedings
  • © 2010

Overview

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6317)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: EKAW 2010.

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Table of contents (47 papers)

  1. Knowledge Engineering: Alignment and Identity

  2. Knowledge Acquisition

  3. Collaboration in Knowledge Engineering

  4. Knowledge Engineering: Patterns

  5. Social Aspects and Tagging

  6. Semantic Web, Web of Data and Linked Data

  7. Ontology Evolution / Refinement

  8. Knowledge Access

Other volumes

  1. Knowledge Engineering and Management by the Masses

Keywords

About this book

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.

Editors and Affiliations

  • Cognitive Interaction Technology Excellence Center (CITEC), Universität Bielefeld, Bielefeld, Germany

    Philipp Cimiano

  • IST/DEI, INESC-ID, Lisboa, Portugal

    H. Sofia Pinto

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