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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) |
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|---|---|---|---|---|
| AIIA-2011-Addis.pdf | versione editoriale | Administrator Richiedi una copia |
http://hdl.handle.net/11584/77066
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