Target-driven merging of taxonomies with Atom
作者：
Highlights：
• We propose and evaluate a new approach called Atom for mapping-based taxonomy merging.
• Atom is an asymmetric algorithm that merges a source taxonomy into the target taxonomy.
• We propose to restrict the semantic overlap in the merge result by giving preference to the target taxonomy.
• We use semantic match mappings for an improved merge result.
摘要
Highlights•We propose and evaluate a new approach called Atom for mapping-based taxonomy merging.•Atom is an asymmetric algorithm that merges a source taxonomy into the target taxonomy.•We propose to restrict the semantic overlap in the merge result by giving preference to the target taxonomy.•We use semantic match mappings for an improved merge result.
论文关键词：Data models,Data integration,Taxonomy merging,Database applications
论文评审过程：Received 27 May 2013, Accepted 12 November 2013, Available online 25 November 2013.
论文官网地址：https://doi.org/10.1016/j.is.2013.11.001
