Publications

Detailed Information

Graph Based Aspect Extraction and Rating Classification of Customer Review Data

Cited 2 time in Web of Science Cited 3 time in Scopus
Authors

Jeon, Sung Whan; Lee, Hye Jin; Lee, Hyeonguk; Cho, Sungzoon

Issue Date
2019-04
Publisher
SPRINGER INTERNATIONAL PUBLISHING AG
Citation
DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, Vol.11448 LNCS, pp.186-199
Abstract
This paper introduces graph-based aspect and rating classification, which utilizes multi-modal word co-occurrence network to solve aspect and sentiment classification tasks. Our model consists of three components: (1) word co-occurrence network construction, with aspect and sentiment labels as different modes; (2) dispersion computation for aspects and sentiments, and; (3) feedforward network for classification. Our experiment shows that proposed model outperforms baseline models, Word2Vec and LDA, in both aspect and sentiment classification tasks. Our classification model uses comparatively smaller vector size for representing words and sentences. The proposed model performs better in classifying out of vocabulary contexts.
ISSN
0302-9743
URI
https://hdl.handle.net/10371/187010
DOI
https://doi.org/10.1007/978-3-030-18590-9_13
Files in This Item:
There are no files associated with this item.
Appears in Collections:

Altmetrics

Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Share