Online multiscale-data classification based on multikernel adaptive filtering with application to sentiment analysis

Ran Iwamoto, Masahiro Yukawa

研究成果: Conference contribution

抄録

We present an online method for multiscale data classification, using the multikernel adaptive filtering framework. The target application is Twitter sentiment analysis, which is a notoriously challenging task of natural language processing. This is because (i) each tweet is typically short, and (ii) domain-specific expressions tend to be used. The efficacy of the proposed multiscale online method is studied with dataset of Twitter. Simulation results show that the proposed approach achieves a higher F1 score than the other online-classification methods, and also outperforms the nonlinear support vector machine.

本文言語English
ホスト出版物のタイトルEUSIPCO 2019 - 27th European Signal Processing Conference
出版社European Signal Processing Conference, EUSIPCO
ISBN(電子版)9789082797039
DOI
出版ステータスPublished - 2019 9月
イベント27th European Signal Processing Conference, EUSIPCO 2019 - A Coruna, Spain
継続期間: 2019 9月 22019 9月 6

出版物シリーズ

名前European Signal Processing Conference
2019-September
ISSN(印刷版)2219-5491

Conference

Conference27th European Signal Processing Conference, EUSIPCO 2019
国/地域Spain
CityA Coruna
Period19/9/219/9/6

ASJC Scopus subject areas

  • 信号処理
  • 電子工学および電気工学

フィンガープリント

「Online multiscale-data classification based on multikernel adaptive filtering with application to sentiment analysis」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル