Conference Information
KSEM 2017 : International Conference on Knowledge Science, Engineering and Management
http://www.ksem2017.conferences.academy/
Submission Date:
2017-04-30
Notification Date:
2017-05-28
Conference Date:
2017-08-19
Location:
Melbourne, Australia
Years:
10
CCF: c   CORE: b   QUALIS: b3   Viewed: 13140   Tracked: 37   Attend: 12

Conference Location
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Call For Papers
KSEM 2017 will be co-located with the flagship international AI conference — IJCAI 2017, and be held in Melbourne, Australia on August 19-20, 2017.

KSEM 2017 is the tenth in this series, which builds on the success of nine events of International Conference on Knowledge Science, Engineering and Management in Guilin, China (KSEM 2006); Melbourne, Australia (KSEM 2007); Vienna, Austria (KSEM 2009); Belfast, UK (KSEM 2010); Irvine, USA (KSEM 2011); Dalian, China (KSEM 2013); Sibiu, Romania (KSEM 2014); Chongqing, China (KSEM2015) and Passau, Germany (KSEM 2016).

The aim of this interdisciplinary conference is to provide a forum for researchers in the broad areas of knowledge science, knowledge engineering, and knowledge management to exchange ideas and to report state of the art research results.

Topics

The conference committee invites submissions of applied or theoretical research and application-oriented papers on all topics of KSEM. Topics include, but are not limited to the following:

Knowledge Science

    Knowledge representation and reasoning
    Logics of knowledge; formal analysis of knowledge; reasoning about knowledge
    Knowledge complexity and knowledge metrics
    Commonsense knowledge; nonmonotonic reasoning
    Uncertainty in knowledge (randomness, fuzziness, roughness, vagueness, etc.)
    Reasoning about knowledge in the presence of inconsistency, incompleteness, context-dependency, etc.
    Belief revision and update
    Cognitive foundations of knowledge
    Knowledge in complex systems (e.g. economical and quantum systems)
    Game-theoretical aspects of knowledge; knowledge in multiagent systems
    Formal ontology

Knowledge Engineering

    Knowledge extraction from texts/big data/Web
    Knowledge discovery from very large databases
    Knowledge integration
    Knowledge-based software engineering
    Knowledge-based systems in life sciences
    Conceptual modelling in knowledge-based systems
    Semantic database systems
    Semantic Web
    Content engineering
    Ontological engineering
    Knowledge engineering applications

Knowledge Management

    Knowledge creation and acquisition
    Knowledge verification and validation
    Knowledge dissemination
    Knowledge management systems
    Organizational ontology
    Organizational memory
    Organizational learning
    Knowledge management strategies and practices
    Knowledge management applications
Last updated by Dou Sun in 2017-03-02
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