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Erschienen in:
2006 | OriginalPaper | Buchkapitel
Evaluating the Performance of Text Mining Systems on Real-world Press Archives
verfasst von : Gerhard Paaß, Hugo de Vries
Erschienen in: From Data and Information Analysis to Knowledge Engineering
Verlag: Springer Berlin Heidelberg
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We investigate the performance of text mining systems for annotating press articles in two real-world press archives. Seven commercial systems are tested which recover the categories of a document as well named entities and catchphrases. Using cross-validation we evaluate the precision-recall characteristic. Depending on the depth of the category tree 39–79% breakeven is achieved. For one corpus 45% of the documents can be classified automatically, based on the system’s confidence estimates. In a usability experiment the formal evaluation results are confirmed. It turns out that with respect to some features human annotators exhibit a lower performance than the text mining systems. This establishes a convincing argument to use text mining systems to support indexing of large document collections.