Maximizing text-mining performance

Maximizing text-mining performance

The authors' adaptive resampling approach surpasses previous decision-tree performance and validates the effectiveness of small, pooled local dictionaries. They demonstrate their approach using the Reuters-21578 benchmark data and a real-world customer E-mail routing system.

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE expert 1999-07, Vol.14 (4), p.63-69
Hauptverfasser: Weiss, S.M., Apte, C., Damerau, F.J., Johnson, D.E., Oles, F.J., Goetz, T., Hampp, T.
Format: Artikel
Sprache:eng
Schlagworte:
Benchmarking
Classification tree analysis
Decision trees
Degradation
Dictionaries
Electronic mail
Email
History
Humans
Mood
Nearest neighbor searches
Online information retrieval
Prediction methods
Resampling
Testing
Text categorization
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The authors' adaptive resampling approach surpasses previous decision-tree performance and validates the effectiveness of small, pooled local dictionaries. They demonstrate their approach using the Reuters-21578 benchmark data and a real-world customer E-mail routing system.
ISSN:1094-7167
0885-9000
DOI:10.1109/5254.784086