Unsupervised aspect-based sentiment analysis on Indonesian restaurant reviews

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

8 Citations (Scopus)

Abstract

We address the problem of aspect-based sentiment analysis (ABSA) from Indonesian restaurant reviews due to its usefulness for customer satisfaction applications. The main task is divided into two subtasks: (1) aspect extraction, and (2) aspect sentiment orientation classification. For both subtasks, we propose an unsupervised approach which does not rely too much on hard-core natural language processing tools since Indonesian language is still under-resourced in terms of language technology. Our unsupervised approach employs several techniques in the area of distributional semantics, such as word embeddings and point-wise mutual information.

Original languageEnglish
Title of host publicationProceedings of the 2017 International Conference on Asian Language Processing, IALP 2017
EditorsRong Tong, Minghui Dong, Yanfeng Lu, Yue Zhang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages383-386
Number of pages4
ISBN (Electronic)9781538619803
DOIs
Publication statusPublished - 21 Feb 2018
Event21st International Conference on Asian Language Processing, IALP 2017 - Singapore, Singapore
Duration: 5 Dec 20177 Dec 2017

Publication series

NameProceedings of the 2017 International Conference on Asian Language Processing, IALP 2017
Volume2018-January

Conference

Conference21st International Conference on Asian Language Processing, IALP 2017
CountrySingapore
CitySingapore
Period5/12/177/12/17

Fingerprint Dive into the research topics of 'Unsupervised aspect-based sentiment analysis on Indonesian restaurant reviews'. Together they form a unique fingerprint.

Cite this