Ontology Relation Based Construction Algorithm of Characteristics Level

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 113)

Abstract

In the Chinese opinion mining, the relevant scholars will focus on how to accurately receive the semantic emotion of opinion word as their breakthrough points, but the accurate access to features and characteristics of the relationship between the relatives were few studied. Correlation level analysis of characteristics will play an important role in the following semantic emotion analysis and understanding of the entire review. This paper describes the different concepts and definitions of ontology and characteristics level, and analyzes the existing construction algorithm of characteristics level. Finally, in the comments on the past different Chinese corpus, the word-level feature extraction algorithm proposed an improved method. After the analysis of specific grammatical structure in Chinese, the algorithm finds whether there are different characteristics of hierarchical relationships between the words with specific grammatical structures and Chinese internet commercial searching engine results.

Keywords

Ontology Data mining Characteristics level Algorithm 

Notes

Acknowledgments

This paper is supported by Research Project of Education Department in Guangxi (201010LX455).

References

  1. 1.
    Maoshu N (2007) Mining and studying on semantic understanding based opinions. Excell Master Eng 10:25–28Google Scholar
  2. 2.
    Kim S, Hovy E (2004) Determining the sentiment of opinion. In: Proceedings of the international conference on computational linguisticsGoogle Scholar
  3. 3.
    Tianfang Y, Xiwen C et al (2008) A survey of opinion mining for texts. J Chin Inf Process 22(3):71–80Google Scholar
  4. 4.
    Turney P (2009) Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th annual meeting of the association for computational linguistics. USA, pp 417–424Google Scholar
  5. 5.
    Morinaga S, Yamanishi K, Tateishi, K et al (2009) Mining product reputations on the web. In: Proceedings of knowledge discovery and data mining, Edmonton, pp 341–349Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of Computer and Information ScienceHechi UniversityYizhouChina

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