Knowledge Engineering: Practice and Patterns [electronic resource] : 17th International Conference, EKAW 2010, Lisbon, Portugal, October 11-15, 2010, Proceedings /
European Knowledge Acquisition Workshop(17th :2010 :Lisbon, Portugal)
European Knowledge Acquisition Workshop
Cimiano, Philipp.editor.
Pinto, H. Sofia.editor.
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.
Bibliographic Level Mode of Issuance: Monograph
Includes bibliographical references and index.
Knowledge Engineering: Alignment and Identity -- Pattern-Based Mapping Refinement -- Practical Considerations on Identity for Instance Management in Ontological Investigation -- Knowledge Acquisition -- Involving Business Users in Formal Modeling Using Natural Language Pattern Sentences -- Knowledge Acquisition from Sources of Law in Public Administration -- Enriching the Gene Ontology via the Dissection of Labels Using the Ontology Pre-processor Language -- Collaboration in Knowledge Engineering -- Ontology Development for the Masses: Creating ICD-11 in WebProtégé -- RDFauthor: Employing RDFa for Collaborative Knowledge Engineering -- Knowledge Engineering: Patterns -- Pattern-Based Ontology Transformation Service Exploiting OPPL and OWL-API -- Experimenting with eXtreme Design -- Social Aspects and Tagging -- Weaving a Social Data Web with Semantic Pingback -- Social People-Tagging vs. Social Bookmark-Tagging -- FOLCOM or the Costs of Tagging -- Semantic Web, Web of Data and Linked Data -- Epiphany: Adaptable RDFa Generation Linking the Web of Documents to the Web of Data -- Scaling Up Question-Answering to Linked Data -- Ontology Evolution / Refinement -- Using Semantic Web Resources for Data Quality Management -- Using Ontological Contexts to Assess the Relevance of Statements in Ontology Evolution -- What Is Concept Drift and How to Measure It? -- Knowledge Access -- Mobile Cultural Heritage Guide: Location-Aware Semantic Search -- Semantic Scout: Making Sense of Organizational Knowledge -- Annotation, Retrieval and Natural Language Processing -- Authoring Technical Documents for Effective Retrieval -- A Methodology towards Effective and Efficient Manual Document Annotation: Addressing Annotator Discrepancy and Annotation Quality -- Towards Better Ontological Support for Recognizing Textual Entailment -- Short Papers -- Making Sense of Design Patterns -- Acquiring and Modelling Legal Knowledge Using Patterns: An Application for the Dutch Immigration and Naturalisation Service -- A Model-Driven Approach for Using Templates in OWL Ontologies -- Specialization and Validation of Statecharts in OWL -- Temporal Knowledge Acquisition and Modeling -- Using Machine Learning to Support Continuous Ontology Development -- Handling Markup Overlaps Using OWL -- Ontology Learning for Cost-Effective Large-Scale Semantic Annotation of Web Service Interfaces -- Towards Hybrid Reasoning for Verifying and Validating Multilevel Models -- Representing, Proving and Sharing Trustworthiness of Web Resources Using Veracity -- Enhancing Content-Based Recommendation with the Task Model of Classification -- Extending Open Rating Systems for Ontology Ranking and Reuse -- HyperTwitter: Collaborative Knowledge Engineering via Twitter Messages -- TagSorting: A Tagging Environment for Collaboratively Building Ontologies -- QuiKey – An Efficient Semantic Command Line -- Kali-ma: A Semantic Guide to Browsing and Accessing Functionalities in Plugin-Based Tools -- Constructing Understandable Explanations for Semantic Search Results -- Ontology Engineering with Rough Concepts and Instances -- Building Large Lexicalized Ontologies from Text: A Use Case in Automatic Indexing of Biotechnology Patents -- ReBEC: A Method for Capturing Experience during Software Development Projects -- Reasoning by Analogy in the Generation of Domain Acceptable Ontology Refinements -- Evaluations of User-Driven Ontology Summarization -- A Visualization Service for the Semantic Web -- How Much Semantic Data on Small Devices? -- A Semantic Approach for Learning Objects Repositories with Knowledge Reuse.
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.
Artificial intelligence.
Computer communication systems.
Software engineering.
Application software.
Information storage and retrieval.
Artificial Intelligence.
Computer Communication Networks.
Software Engineering/Programming and Operating Systems.
Information Systems Applications (incl. Internet).
Information Storage and Retrieval.
Computer Appl. in Administrative Data Processing.

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