Model-Based Knowledge Searching

Maxim Bragilovski, Yifat Makias, Moran Shamshila, Roni Stern, Arnon Sturm

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

Abstract

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.

Original languageAmerican English
Title of host publicationConceptual Modeling - 40th International Conference, ER 2021, Proceedings
EditorsAditya Ghose, Jennifer Horkoff, Vítor E. Silva Souza, Jeffrey Parsons, Joerg Evermann
PublisherSpringer Science and Business Media Deutschland GmbH
Pages242-256
Number of pages15
ISBN (Print)9783030890216
DOIs
StatePublished - 16 Oct 2021
Event40th International Conference on Conceptual Modeling, ER 2021 - Virtual, Online
Duration: 18 Oct 202121 Oct 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13011 LNCS

Conference

Conference40th International Conference on Conceptual Modeling, ER 2021
CityVirtual, Online
Period18/10/2121/10/21

Keywords

  • Conceptual modeling
  • Matching
  • Searching

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'Model-Based Knowledge Searching'. Together they form a unique fingerprint.

Cite this