Comparison of Schema Matching Evaluations

By Hong Hai Do, Sergey Melnik, Erhard Rahm. Web, Web-Services, and Database Systems, 2002

519 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/587a44430d4111bb8b2eff5646b22bd1ed6b620d

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Citations in the corpus

Ontology Alignment Evaluation Initiative: Six Years of Experience (2011, background): “The closest to OAEI works on benchmarking of database schema matching systems are those of [16] and more recently of XBenchMatch [18; 17]; though these initiatives have not led to well-established recurrent evaluation campaigns.”
A Survey of Schema-Based Matching Approaches (2005, unknown): “At present, S-Match libraries contain 13 element-level matchers, see [23], and 2 structure-level (JSAT and SAT4J) matchers.”
TEGRA: Table Extraction by Global Record Alignment (2015, background): “It has been shown [15,18] that in certain matching and alignment problems, traditional precision/recall is not suitable, and generalized P/R evaluations has been proposed [15, 18].”
Ontology Mapping - An Integrated Approach (2004, methodology): “The definitions of precision and recall is adapted by us to fit the given evalua tion scenario [8].”
QOM - Quick Ontology Mapping (2004, background): “[17]): Precision p = #correct found mapping #found mappings Recall r = #correct found mappings #existing mappings F-Measure f1 = 2pr p+r”
Generic schema matching, ten years later (2011, background): “Match tools have been intensively evaluated but typically under different conditions and for smaller match problems [4][18].”
Ontology change: classification and survey (2008, background): “Evaluations of such works appear in (Avesani et al. 2005), (Do et al. 2002), (Svab et al. 2007), (Yatskevich 2003).”
iMAP: discovering complex semantic matches between database schemas (2004, methodology): “Several prior works [8, 7] employ the notion of precision and recall to evaluate matching algorithms.”
S-Match: an Algorithm and an Implementation of Semantic Matching (2004, methodology): “As match quality measures we have used the following indicators: precision, recall, overall, F-measure, overall (from [ 8 ]) and time (from [19]).”
An API for Ontology Alignment (2004, methodology): “PRecEvaluator, which implements a classical precision/recall/fallout evaluation as well as the derived measures introduced in [3].”
A String Metric for Ontology Alignment (2005, methodology): “Many times during the experiments we faced situations where several runs of an alignment between two ontologies using the same configuration produced different precision and recall [16] values cause of this phenomenon.”