Effective kernelized online learning in language processing tasks

Simone Filice, Giuseppe Castellucci, Danilo Croce, Roberto Basili

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Kernel-based methods for NLP tasks have been shown to enable robust and effective learning, although their inherent complexity is manifest also in Online Learning (OL) scenarios, where time and memory usage grows along with the arrival of new examples. A state-of-the-art budgeted OL algorithm is here extended to efficiently integrate complex kernels by constraining the overall complexity. Principles of Fairness and Weight Adjustment are applied to mitigate imbalance in data and improve the model stability. Results in Sentiment Analysis in Twitter and Question Classification show that performances very close to the state-of-the-art achieved by batch algorithms can be obtained.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages347-358
Number of pages12
Volume8416 LNCS
ISBN (Print)9783319060279
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event36th European Conference on Information Retrieval, ECIR 2014 - Amsterdam
Duration: 13 Apr 201416 Apr 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8416 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other36th European Conference on Information Retrieval, ECIR 2014
CityAmsterdam
Period13/4/1416/4/14

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Filice, S., Castellucci, G., Croce, D., & Basili, R. (2014). Effective kernelized online learning in language processing tasks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8416 LNCS, pp. 347-358). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8416 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-06028-6_29