UNICA IRIS Institutional Research Information System
IRIS è il sistema di gestione integrata dei dati della ricerca (persone, progetti, pubblicazioni, attività) adottato dall'Università degli Studi di Cagliari dal mese di luglio 2015.
EnglishThresholding strategies in automated text categorization are an underexplored area of research. Indeed, thresholding strategies are often considered a post-processing step of minor importance, the underlying assumptions being that they do not make a difference in the performance of a classifier and that finding the optimal thresholding strategy for any given classifier is trivial. Neither these assumptions are true. In this paper, we concentrate on progressive filtering, a hierarchical text categorization technique that relies on a local-classifier-per-node approach, thus mimicking the underlying taxonomy of categories. The focus of the paper is on assessing TSA, a greedy threshold selection algorithm, against a relaxed brute-force algorithm and the most relevant state-of-the-art algorithms. Experiments, performed on Reuters, confirm the validity of TSA.
A comparative study of thresholding strategies in progressive filtering / Addis A; Armano G; Vargiu E. - 6934(2011), pp. 10-20.
| Titolo: | A comparative study of thresholding strategies in progressive filtering |
| Autori: | |
| Data di pubblicazione: | 2011 |
| Rivista: | |
| Citazione: | A comparative study of thresholding strategies in progressive filtering / Addis A; Armano G; Vargiu E. - 6934(2011), pp. 10-20. |
| Handle: | http://hdl.handle.net/11584/77066 |
| ISBN: | 978-3-642-23953-3 |
| Tipologia: | 2.1 Contributo in volume (Capitolo o Saggio) |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| AIIA-2011-Addis.pdf | versione editoriale | Administrator Richiedi una copia |
http://hdl.handle.net/11584/77066
Copyright © 2021