TY - GEN
T1 - Conmerge – arbitration of constraint-based knowledge bases
AU - Uta, Mathias
AU - Felfernig, Alexander
PY - 2020/1/1
Y1 - 2020/1/1
N2 - 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.
AB - 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.
KW - Arbitration
KW - Constraint-based configuration
KW - Merging knowledge bases
UR - http://www.scopus.com/inward/record.url?scp=85091271039&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-55789-8_12
DO - 10.1007/978-3-030-55789-8_12
M3 - Conference paper
AN - SCOPUS:85091271039
SN - 9783030557881
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 127
EP - 139
BT - Trends 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
A2 - Fujita, Hamido
A2 - Sasaki, Jun
A2 - Fournier-Viger, Philippe
A2 - Ali, Moonis
PB - Springer Science and Business Media Deutschland GmbH
T2 - 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020
Y2 - 22 September 2020 through 25 September 2020
ER -