TY - GEN
T1 - Model-Based Knowledge Searching
AU - Bragilovski, Maxim
AU - Makias, Yifat
AU - Shamshila, Moran
AU - Stern, Roni
AU - Sturm, Arnon
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021/10/16
Y1 - 2021/10/16
N2 - As knowledge increases tremendously each and every day, there is a need for means to manage and organize it, so as to utilize it when needed. For example, for finding solutions to technical/engineering problems. An alternative for achieving this goal is through knowledge mapping that aims at indexing the knowledge. Nevertheless, searching for knowledge in such maps is still a challenge. In this paper, we propose an algorithm for knowledge searching over maps created by ME-MAP, a mapping approach we developed. The algorithm is a greedy one that aims at maximizing the similarity between a query and existing knowledge encapsulated in ME-maps. We evaluate the efficiency of the algorithm in comparison to an expert judgment. The evaluation indicates that the algorithm achieved high performance within a bounded time. Though additional examination is required, the sought algorithm can be easily adapted to other modeling languages for searching models.
AB - As knowledge increases tremendously each and every day, there is a need for means to manage and organize it, so as to utilize it when needed. For example, for finding solutions to technical/engineering problems. An alternative for achieving this goal is through knowledge mapping that aims at indexing the knowledge. Nevertheless, searching for knowledge in such maps is still a challenge. In this paper, we propose an algorithm for knowledge searching over maps created by ME-MAP, a mapping approach we developed. The algorithm is a greedy one that aims at maximizing the similarity between a query and existing knowledge encapsulated in ME-maps. We evaluate the efficiency of the algorithm in comparison to an expert judgment. The evaluation indicates that the algorithm achieved high performance within a bounded time. Though additional examination is required, the sought algorithm can be easily adapted to other modeling languages for searching models.
KW - Conceptual modeling
KW - Matching
KW - Searching
UR - http://www.scopus.com/inward/record.url?scp=85118103058&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-89022-3_20
DO - 10.1007/978-3-030-89022-3_20
M3 - Conference contribution
AN - SCOPUS:85118103058
SN - 9783030890216
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 242
EP - 256
BT - Conceptual Modeling - 40th International Conference, ER 2021, Proceedings
A2 - Ghose, Aditya
A2 - Horkoff, Jennifer
A2 - Silva Souza, Vítor E.
A2 - Parsons, Jeffrey
A2 - Evermann, Joerg
PB - Springer Science and Business Media Deutschland GmbH
T2 - 40th International Conference on Conceptual Modeling, ER 2021
Y2 - 18 October 2021 through 21 October 2021
ER -