Home |  English version |  Mappa |  Commenti |  Sondaggio |  Staff |  Contattaci Cerca nel sito  
Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

Torna all'elenco Report e working Paper anno 2019

Report e working Paper

Tipo: Rapporto di ricerca (Research report)

Titolo: Learning to weight for text classification

Anno di pubblicazione: 2019

Formato: Elettronico

Autori: Moreo Fernández A.D.; Esuli A.; Sebastiani F.

Affiliazioni autori: CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy

Autori CNR:

  • ANDREA ESULI
  • ALEJANDRO DAVID MOREO FERNANDEZ
  • FABRIZIO SEBASTIANI

Lingua: inglese

Sintesi: In information retrieval (IR) and related tasks, term weighting approaches typically consider the frequency of the term in the document and in the collection in order to compute a score reflecting the importance of the term for the document. In tasks characterized by the presence of training data (such as text classification) it seems logical that the term weighting function should take into account the distribution (as estimated from training data) of the term across the classes of interest. Although `supervised term weighting' approaches that use this intuition have been described before, they have failed to show consistent improvements. In this article we analyse the possible reasons for this failure, and call consolidated assumptions into question. Following this criticism we propose a novel supervised term weighting approach that, instead of relying on any predefined formula, learns a term weighting function optimised on the training set of interest; we dub this approach Learning to Weight (LTW). The experiments that we run on several well-known benchmarks, and using different learning methods, show that our method outperforms previous term weighting approaches in text classification.

Lingua sintesi: eng

Pagine totali: 16

Parole chiave:

  • Text classification; Deep learning

URL: https://arxiv.org/abs/1903.12090

ID report/working paper: arXiv:1903.12090 [cs.LG]

Strutture CNR:

Moduli:

Allegati: Learning to Weight for Text Classification (application/pdf)
Preprint

 
Torna indietro Richiedi modifiche Invia per email Stampa
Home Il CNR  |  I servizi News |   Eventi | Istituti |  Focus