Semantic aspect discovery for online reviews

Md Hijbul Alam, Sang-Geun Lee

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

10 Citations (Scopus)

Abstract

The number of opinions and reviews about different products and services is growing online. Users frequently look for important aspects of a product or service in the reviews. Usually, they are interested in semantic (i.e., sentiment-oriented) aspects. However, extracting semantic aspects with supervised methods is very expensive. We propose a domain independent unsupervised model to extract semantic aspects, and conduct qualitative and quantitative experiments to evaluate the extracted aspects. The experiments show that our model effectively extracts semantic aspects with correlated top words. In addition, the conducted evaluation on aspect sentiment classification shows that our model outperforms other models by 5-7% in terms of macro-average F1.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Data Mining, ICDM
Pages816-821
Number of pages6
DOIs
Publication statusPublished - 2012 Dec 1
Event12th IEEE International Conference on Data Mining, ICDM 2012 - Brussels, Belgium
Duration: 2012 Dec 102012 Dec 13

Other

Other12th IEEE International Conference on Data Mining, ICDM 2012
CountryBelgium
CityBrussels
Period12/12/1012/12/13

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Semantics
Macros
Experiments

Keywords

  • Aspect discovery
  • Opinion mining
  • Sentiment analysis
  • Topic model

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Alam, M. H., & Lee, S-G. (2012). Semantic aspect discovery for online reviews. In Proceedings - IEEE International Conference on Data Mining, ICDM (pp. 816-821). [6413739] https://doi.org/10.1109/ICDM.2012.65

Semantic aspect discovery for online reviews. / Alam, Md Hijbul; Lee, Sang-Geun.

Proceedings - IEEE International Conference on Data Mining, ICDM. 2012. p. 816-821 6413739.

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

Alam, MH & Lee, S-G 2012, Semantic aspect discovery for online reviews. in Proceedings - IEEE International Conference on Data Mining, ICDM., 6413739, pp. 816-821, 12th IEEE International Conference on Data Mining, ICDM 2012, Brussels, Belgium, 12/12/10. https://doi.org/10.1109/ICDM.2012.65
Alam MH, Lee S-G. Semantic aspect discovery for online reviews. In Proceedings - IEEE International Conference on Data Mining, ICDM. 2012. p. 816-821. 6413739 https://doi.org/10.1109/ICDM.2012.65
Alam, Md Hijbul ; Lee, Sang-Geun. / Semantic aspect discovery for online reviews. Proceedings - IEEE International Conference on Data Mining, ICDM. 2012. pp. 816-821
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