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Phrase dependency parsing for opinion mining

Authors:

Xuanjing Huang,

Lide WuAuthors Info & Claims

EMNLP '09: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3

Pages 1533 - 1541

Published: 06 August 2009 Publication History

Abstract

In this paper, we present a novel approach for mining opinions from product reviews, where it converts opinion mining task to identify product features, expressions of opinions and relations between them. By taking advantage of the observation that a lot of product features are phrases, a concept of phrase dependency parsing is introduced, which extends traditional dependency parsing to phrase level. This concept is then implemented for extracting relations between product features and expressions of opinions. Experimental evaluations show that the mining task can benefit from phrase dependency parsing.

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Cited By

Gutierrez CWhittaker APatenio KGehman JLefsrud LBarbosa DStroulia EOnuţ IZulkernine F(2021)Analyzing and visualizing Twitter conversationsProceedings of the 31st Annual International Conference on Computer Science and Software Engineering10.5555/3507788.3507791(4-13)Online publication date: 22-Nov-2021
https://dl.acm.org/doi/10.5555/3507788.3507791
Rani SKumar P(2021)Aspect-based Sentiment Analysis using Dependency ParsingACM Transactions on Asian and Low-Resource Language Information Processing10.1145/348524321:3(1-19)Online publication date: 13-Dec-2021
https://dl.acm.org/doi/10.1145/3485243
Wang WPan S(2020)Syntactically Meaningful and Transferable Recursive Neural Networks for Aspect and Opinion ExtractionComputational Linguistics10.1162/coli_a_0036245:4(705-736)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1162/coli_a_00362
Show More Cited By

Index Terms

Phrase dependency parsing for opinion mining
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems
  1. Information retrieval
    1. Document representation
      1. Content analysis and feature selection
    2. Evaluation of retrieval results
  2. Information systems applications
    1. Data mining

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Information & Contributors

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Published In

cover image DL Hosted proceedings

EMNLP '09: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3

August 2009

573 pages

ISBN:9781932432633

Program Chairs:
Philipp Koehn
University of Edinburgh
,
Rada Mihalcea
University of North Texas

Publisher

Association for Computational Linguistics

United States

Publication History

Published: 06 August 2009

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Research-article

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Overall Acceptance Rate 73 of 234 submissions, 31%

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Cited By

Gutierrez CWhittaker APatenio KGehman JLefsrud LBarbosa DStroulia EOnuţ IZulkernine F(2021)Analyzing and visualizing Twitter conversationsProceedings of the 31st Annual International Conference on Computer Science and Software Engineering10.5555/3507788.3507791(4-13)Online publication date: 22-Nov-2021
https://dl.acm.org/doi/10.5555/3507788.3507791
Rani SKumar P(2021)Aspect-based Sentiment Analysis using Dependency ParsingACM Transactions on Asian and Low-Resource Language Information Processing10.1145/348524321:3(1-19)Online publication date: 13-Dec-2021
https://dl.acm.org/doi/10.1145/3485243
Wang WPan S(2020)Syntactically Meaningful and Transferable Recursive Neural Networks for Aspect and Opinion ExtractionComputational Linguistics10.1162/coli_a_0036245:4(705-736)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1162/coli_a_00362
Lee CBae HCha KLim G(2020)Unsupervised Method for Measuring Smart Home Service Quality through Gap Analysis and Dependency ParsingThe 9th International Conference on Smart Media and Applications10.1145/3426020.3426062(167-171)Online publication date: 17-Sep-2020
https://dl.acm.org/doi/10.1145/3426020.3426062
Xue HWang QLuo BSeo HLi F(2019)Content-Aware Trust Propagation Toward Online Review Spam DetectionJournal of Data and Information Quality10.1145/330525811:3(1-31)Online publication date: 20-Jun-2019
https://dl.acm.org/doi/10.1145/3305258
Luo HLi TLiu BWang BUnger H(2019)Improving Aspect Term Extraction With Bidirectional Dependency Tree RepresentationIEEE/ACM Transactions on Audio, Speech and Language Processing10.1109/TASLP.2019.291309427:7(1201-1212)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1109/TASLP.2019.2913094
Agathangelou PKatakis IKoutoulakis IKokkoras FGunopulos D(2018)Learning patterns for discovering domain-oriented opinion wordsKnowledge and Information Systems10.1007/s10115-017-1072-y55:1(45-77)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1007/s10115-017-1072-y
Wang WPan SDahlmeier DXiao XSingh SMarkovitch S(2017)Coupled multi-layer attentions for co-extraction of aspect and opinion termsProceedings of the Thirty-First AAAI Conference on Artificial Intelligence10.5555/3298023.3298050(3316-3322)Online publication date: 4-Feb-2017
https://dl.acm.org/doi/10.5555/3298023.3298050
Cheng JZhao SZhang JKing IZhang XWang HLim EWinslett MSanderson MFu ASun JCulpepper SLo EHo JDonato DAgrawal RZheng YCastillo CSun ATseng VLi C(2017)Aspect-level Sentiment Classification with HEAT (HiErarchical ATtention) NetworkProceedings of the 2017 ACM on Conference on Information and Knowledge Management10.1145/3132847.3133037(97-106)Online publication date: 6-Nov-2017
https://dl.acm.org/doi/10.1145/3132847.3133037
Yao YZhao WWang YTong HXu FLu J(2017)Version-Aware Rating Prediction for Mobile App RecommendationACM Transactions on Information Systems10.1145/301545835:4(1-33)Online publication date: 23-Jun-2017
https://dl.acm.org/doi/10.1145/3015458
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