
Finding alignments between ontologies is a very important operation for ontology engineering. It allows for establishing links between ontologies, either to integrate them in an application or to relate developed ontologies to context. It is even more critical for networked ontologies. Incorrect alignments may lead to unwanted consequences throughout the whole network and incomplete alignments may fail to provide the expected consequences. Yet, there is no well established methodology available for matching ontologies. We propose methodological guidelines that build on previously disconnected results and experiences.
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], 330, [INFO.INFO-WB] Computer Science [cs]/Web, [INFO.INFO-WB]Computer Science [cs]/Web, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 004
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], 330, [INFO.INFO-WB] Computer Science [cs]/Web, [INFO.INFO-WB]Computer Science [cs]/Web, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 004
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
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| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
