Efficient User Involvement in Semiautomatic Ontology Matching

Xingsi XUE, Junfeng CHEN, Xin YAO

Research output: Journal PublicationsJournal Article (refereed)peer-review


Semiautomatic ontology matching poses a new challenge of how to implement an efficient user interactions. To address this challenge, we answer three questions in this paper: (1) when should we activate the interacting process; (2) which correspondences should be presented for user validation; and (3) how to make use of the validating results. In particular, we present an interactive compact memetic algorithm (ICMA) based semiautomatic ontology matching technique to: (1) determine the timing of getting a user involved; (2) determine the problematic correspondences; and (3) propagate the user validating results. The experimental results show that three proposed strategies can effectively reduce the user's workload and the algorithm's runtime, increase the alignment's quality, and the performance of ICMA outperforms the state-of-the-art semiautomatic ontology matching techniques.
Original languageEnglish
Pages (from-to)214-224
Number of pages11
JournalIEEE Transactions on Emerging Topics in Computational Intelligence
Issue number2
Publication statusPublished - Apr 2021
Externally publishedYes


  • Semiautomatic ontology matching
  • interactive compact memetic algorithm
  • user involvement


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