Publication | Closed Access
On the evaluation of document analysis components by recall, precision, and accuracy
181
Citations
9
References
1999
Year
Unknown Venue
EngineeringComparative TestCorpus LinguisticsText MiningTest SampleNatural Language ProcessingInformation RetrievalData ScienceDocument AnalysisComputational LinguisticsLanguage TestingDocument ClassificationStructured DocumentAbsolute EffectivenessLanguage StudiesContent AnalysisStatisticsEvaluation MeasureSoftware TestingDocument Analysis ComponentsText ProcessingTest CollectionLinguisticsDocument Processing
In document analysis, it is common to prove the usefulness of a component by an experimental evaluation. By applying the respective algorithms to a test sample, effectiveness measures such as recall, precision, and accuracy are computed. The goal of such an evaluation is two-fold: on the one hand it shows that the absolute effectiveness of the algorithm is acceptable for practical use. On the other hand the evaluation can prove that the algorithm has a better or worse effectiveness than another algorithm. We argue that the experimental evaluation on relative small test sets-as is very common in document analysis has to be taken with extreme care from a statistical point of view. In fact, it is surprising how weak statements derived from such evaluations are.
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