A convolutional neural network based sentiment classification and the convolutional kernel representation

Shen Gao, Huaping Zhang*, Kai Gao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper presents a multiple layer based convolutional neural network for sentiment analysis. Word embedding is present to learn the features and representations. This paper also presents a convolutional kernel representation for textual data. In order to evaluate the performance, this paper uses short-text corpus to evaluate. Experimental results show the feasibility of the approach.

Original languageEnglish
Title of host publicationNatural Language Processing and Information Systems - 22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017, Proceedings
EditorsFlavius Frasincar, Ashwin Ittoo, Elisabeth Metais, Le Minh Nguyen
PublisherSpringer Verlag
Pages287-291
Number of pages5
ISBN (Print)9783319595689
DOIs
Publication statusPublished - 2017
Event22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017 - Liege, Belgium
Duration: 21 Jun 201723 Jun 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10260 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017
Country/TerritoryBelgium
CityLiege
Period21/06/1723/06/17

Keywords

  • Classification
  • Convolutional neural network
  • Representation
  • Sentiment analysis
  • Word embedding

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