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Combining existential rules with the power of CP-theories

Published: 25 July 2015 Publication History

Abstract

The tastes of a user can be represented in a natural way by using qualitative preferences. In this paper, we explore how ontological knowledge expressed via existential rules can be combined with CP-theories to (i) represent qualitative preferences along with domain knowledge, and (ii) perform preference-based answering of conjunctive queries (CQs). We call these combinations ontological CP-theories (OCP-theories). We define skyline and k-rank answers to CQs based on the user's preferences encoded in an OCP-theory, and provide an algorithm for computing them. We also provide precise complexity (including data tractability) results for deciding consistency, dominance, and CQ skyline membership for OCP-theories.

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  • (2018)More Complexity Results about Reasoning over ( m )CP-netsProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3237383.3237930(1540-1548)Online publication date: 9-Jul-2018
  • (2017)Knowledge engineering for intelligent decision supportProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171837.3172029(5131-5135)Online publication date: 19-Aug-2017
  • (2017)Query answering in ontologies under preference rankingsProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171642.3171777(943-949)Online publication date: 19-Aug-2017
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  1. Combining existential rules with the power of CP-theories

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    Published In

    cover image Guide Proceedings
    IJCAI'15: Proceedings of the 24th International Conference on Artificial Intelligence
    July 2015
    4429 pages
    ISBN:9781577357384

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    • The International Joint Conferences on Artificial Intelligence, Inc. (IJCAI)

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    AAAI Press

    Publication History

    Published: 25 July 2015

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    View all
    • (2018)More Complexity Results about Reasoning over ( m )CP-netsProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3237383.3237930(1540-1548)Online publication date: 9-Jul-2018
    • (2017)Knowledge engineering for intelligent decision supportProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171837.3172029(5131-5135)Online publication date: 19-Aug-2017
    • (2017)Query answering in ontologies under preference rankingsProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171642.3171777(943-949)Online publication date: 19-Aug-2017
    • (2017)Auto-Encoding User Ratings via Knowledge Graphs in Recommendation ScenariosProceedings of the 2nd Workshop on Deep Learning for Recommender Systems10.1145/3125486.3125496(60-66)Online publication date: 27-Aug-2017
    • (2016)Preferential query answering in the semantic web with possibilistic networksProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence10.5555/3060621.3060759(994-1000)Online publication date: 9-Jul-2016

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