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文章基本信息

  • 标题:Aspect Clustering Combined N-gram for Reviews
  • 本地全文:下载
  • 作者:Shibo Zhang ; Xiaojie Wang
  • 期刊名称:The Open Cybernetics & Systemics Journal
  • 电子版ISSN:1874-110X
  • 出版年度:2014
  • 卷号:8
  • 期号:1
  • 页码:938-943
  • DOI:10.2174/1874110X01408010938
  • 出版社:Bentham Science Publishers Ltd
  • 摘要:

    With the increase in popularity of e-commerce, more and more customer reviews are available online, it’s usually hard to go through each of them. Latent Dirichlet Allocation (LDA) was used to mine product aspect. Considering the weakness of standard LDA when processing review text, we defined the product aspect model, and predefined aspects for different domains, and proposed aspect model combined N-gram based on sentence, which can automate aspect clustering. Our experimental results show that the proposed model can cluster mostly aspects and recognize representative words for the aspect with more than one word, and achieve better sentence-level aspect precision than previously proposed aspect models.

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