EKAW 2020: Difference between revisions

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==Topics==
==Topics==


Ethical and Trustworthy Knowledge Engineering
'''Ethical and Trustworthy Knowledge Engineering'''


    Ethics and trust in automated reasoning
*Ethics and trust in automated reasoning
    Algorithmic transparency and explanations for knowledge-based systems
*Algorithmic transparency and explanations for knowledge-based systems
    Knowledge and ethics
*Knowledge and ethics
    Ontologies for trust and ethics
*Ontologies for trust and ethics
    Trust and privacy in knowledge representation
*Trust and privacy in knowledge representation <br>


Knowledge Engineering and Acquisition
'''Knowledge Engineering and Acquisition'''


    Tools and methodologies for ontology engineering
*Tools and methodologies for ontology engineering
    Ontology design patterns
*Ontology design patterns
    Ontology localisation
*Ontology localisation
    Multilinguality in ontologies
*Multilinguality in ontologies
    Ontology alignment
*Ontology alignment
    Knowledge authoring and semantic annotation
*Knowledge authoring and semantic annotation
    Knowledge acquisition from non-ontological resources (thesauri, folksonomies, etc.)
*Knowledge acquisition from non-ontological resources (thesauri, folksonomies, etc.)
    Semi-automatic knowledge acquisition, e.g., ontology learning
*Semi-automatic knowledge acquisition, e.g., ontology learning
    Collaborative knowledge acquisition and formalisation
*Collaborative knowledge acquisition and formalisation
    Mining the Semantic Web and the Web of Data
*Mining the Semantic Web and the Web of Data
    Ontology evaluation and metrics
*Ontology evaluation and metrics
    Uncertainty and vagueness in knowledge representation
*Uncertainty and vagueness in knowledge representation
    Dealing with dynamic, distributed and emerging knowledge
*Dealing with dynamic, distributed and emerging knowledge <br>


Knowledge Management
'''Knowledge Management'''


    Methodologies and tools for knowledge management
*Methodologies and tools for knowledge management
    Knowledge sharing and distribution, collaboration
*Knowledge sharing and distribution, collaboration
    Best practices and lessons learned from case studies
*Best practices and lessons learned from case studies
    Provenance and trust in knowledge management
*Provenance and trust in knowledge management
    FAIR data and knowledge
*FAIR data and knowledge
    Methods for accelerating take-up of knowledge management technologies
*Methods for accelerating take-up of knowledge management technologies
    Corporate memories for knowledge management
*Corporate memories for knowledge management
    Knowledge evolution, maintenance and preservation
*Knowledge evolution, maintenance and preservation
    Incentives for human knowledge acquisition and data quality improvement (e.g. games with a purpose)
*Incentives for human knowledge acquisition and data quality improvement (e.g. games with a purpose) <br>


Social and Cognitive Aspects of Knowledge Representation
'''Social and Cognitive Aspects of Knowledge Representation'''


    Similarity and analogy-based reasoning
*Similarity and analogy-based reasoning
    Knowledge representation inspired by cognitive science
*Knowledge representation inspired by cognitive science
    Synergies between humans and machines
*Synergies between humans and machines
    Knowledge emerging from user interaction and networks
*Knowledge emerging from user interaction and networks
    Knowledge ecosystems
*Knowledge ecosystems
    Expert finding, e.g., by social network analysis
*Expert finding, e.g., by social network analysis
    Collaborative and social approaches to knowledge management and acquisition
*Collaborative and social approaches to knowledge management and acquisition
    Crowdsourcing in knowledge management
*Crowdsourcing in knowledge management <br>


Knowledge discovery
'''Knowledge discovery'''


    Mining patterns and association rules
*Mining patterns and association rules
    Mining complex data: numbers, sequences, trees, graphs
*Mining complex data: numbers, sequences, trees, graphs
    Formal Concept Analysis and extensions
*Formal Concept Analysis and extensions
    Numerical data mining methods and knowledge processing
*Numerical data mining methods and knowledge processing
    Mining the web of data for knowledge construction
*Mining the web of data for knowledge construction
    Text mining and ontology engineering
*Text mining and ontology engineering
    Classification and clustering for knowledge management
*Classification and clustering for knowledge management
    Symbolic and sub-symbolic learning machine learning  
*Symbolic and sub-symbolic learning machine learning <br>


Applications in specific domains such as
'''Applications in specific domains such as'''
 
*eGovernment and public administration
*Life sciences, health and medicine
*Humanities and Social Sciences
*Automotive and manufacturing industry
*Cultural heritage
*Digital libraries
*Geosciences
*ICT4D (Knowledge in the developing world)<br>


    eGovernment and public administration
    Life sciences, health and medicine
    Humanities and Social Sciences
    Automotive and manufacturing industry
    Cultural heritage
    Digital libraries
    Geosciences
    ICT4D (Knowledge in the developing world)


==Submissions==
==Submissions==

Revision as of 11:02, 17 February 2020

EKAW 2020
22nd International Conference on Knowledge Engineering and Knowledge Management
Event in series EKAW
Dates 2020/09/16 (iCal) - 2020/09/20
Homepage: https://ekaw2020.inf.unibz.it/
Location
Location: Bozen-Bolzano, Italy
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Table of Contents


22nd International Conference on Knowledge Engineering and Knowledge Management

Topics

Ethical and Trustworthy Knowledge Engineering

  • Ethics and trust in automated reasoning
  • Algorithmic transparency and explanations for knowledge-based systems
  • Knowledge and ethics
  • Ontologies for trust and ethics
  • Trust and privacy in knowledge representation

Knowledge Engineering and Acquisition

  • Tools and methodologies for ontology engineering
  • Ontology design patterns
  • Ontology localisation
  • Multilinguality in ontologies
  • Ontology alignment
  • Knowledge authoring and semantic annotation
  • Knowledge acquisition from non-ontological resources (thesauri, folksonomies, etc.)
  • Semi-automatic knowledge acquisition, e.g., ontology learning
  • Collaborative knowledge acquisition and formalisation
  • Mining the Semantic Web and the Web of Data
  • Ontology evaluation and metrics
  • Uncertainty and vagueness in knowledge representation
  • Dealing with dynamic, distributed and emerging knowledge

Knowledge Management

  • Methodologies and tools for knowledge management
  • Knowledge sharing and distribution, collaboration
  • Best practices and lessons learned from case studies
  • Provenance and trust in knowledge management
  • FAIR data and knowledge
  • Methods for accelerating take-up of knowledge management technologies
  • Corporate memories for knowledge management
  • Knowledge evolution, maintenance and preservation
  • Incentives for human knowledge acquisition and data quality improvement (e.g. games with a purpose)

Social and Cognitive Aspects of Knowledge Representation

  • Similarity and analogy-based reasoning
  • Knowledge representation inspired by cognitive science
  • Synergies between humans and machines
  • Knowledge emerging from user interaction and networks
  • Knowledge ecosystems
  • Expert finding, e.g., by social network analysis
  • Collaborative and social approaches to knowledge management and acquisition
  • Crowdsourcing in knowledge management

Knowledge discovery

  • Mining patterns and association rules
  • Mining complex data: numbers, sequences, trees, graphs
  • Formal Concept Analysis and extensions
  • Numerical data mining methods and knowledge processing
  • Mining the web of data for knowledge construction
  • Text mining and ontology engineering
  • Classification and clustering for knowledge management
  • Symbolic and sub-symbolic learning machine learningÂ

Applications in specific domains such as

  • eGovernment and public administration
  • Life sciences, health and medicine
  • Humanities and Social Sciences
  • Automotive and manufacturing industry
  • Cultural heritage
  • Digital libraries
  • Geosciences
  • ICT4D (Knowledge in the developing world)


Submissions

Important Dates

Committees

  • Co-Organizers
  • General Co-Chairs
  • Local Organizing Co-Chairs
  • Program Committee Members