Conmerge – arbitration of constraint-based knowledge bases

Mathias Uta*, Alexander Felfernig

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Due to the increasing need to individualize mass products, product configurators are becoming more and more a manifest in the environment of business to customer retailers. Furthermore, technology-driven companies try to formalize expert knowledge to maintain their most valuable asset – their technological know-how. Consequently, insulated and diversified knowledge bases are created leading to complex challenges whenever knowledge needs to be consolidated. In this paper, we present the ConMerge-Algorithm which can integrate two constraint-based knowledge bases by applying redundancy detection and conflict detection. Based on detected conflicts, our algorithm applies resolution strategies and assures consistency of the resulting knowledge bases. Furthermore, the user can choose the operation mode of the algorithm: keeping all configuration solutions of each individual input knowledge base or only solutions which are valid in both original knowledge bases. With this method of knowledge base arbitration, the ability to consolidating distributed product configuration knowledge bases is provided.

Original languageEnglish
Title of host publicationTrends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices - 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020, Proceedings
EditorsHamido Fujita, Jun Sasaki, Philippe Fournier-Viger, Moonis Ali
PublisherSpringer Science and Business Media Deutschland GmbH
Pages127-139
Number of pages13
ISBN (Print)9783030557881
DOIs
Publication statusPublished - 1 Jan 2020
Event33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020 - Kitakyushu, Japan
Duration: 22 Sep 202025 Sep 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12144 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020
Country/TerritoryJapan
CityKitakyushu
Period22/09/2025/09/20

Keywords

  • Arbitration
  • Constraint-based configuration
  • Merging knowledge bases

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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