Towards a Chinese Common and Common Sense Knowledge Base for Sentiment Analysis

  • Erik Cambria
  • Amir Hussain
  • Tariq Durrani
  • Jiajun Zhang
Conference paper

DOI: 10.1007/978-3-642-31087-4_46

Volume 7345 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Cambria E., Hussain A., Durrani T., Zhang J. (2012) Towards a Chinese Common and Common Sense Knowledge Base for Sentiment Analysis. In: Jiang H., Ding W., Ali M., Wu X. (eds) Advanced Research in Applied Artificial Intelligence. IEA/AIE 2012. Lecture Notes in Computer Science, vol 7345. Springer, Berlin, Heidelberg

Abstract

To date, the majority of sentiment analysis research has focused on English language. Recent studies, however, show that non-native English speakers heavily support the growing use of Internet. Chinese, specifically, is poised to outpace English as the dominant language online in a few years’ time. So far, just a few isolated research endeavors have been undertaken to meet the demands of real-life Chinese web environments. Natural language processing research endeavor, in fact, primarily depends on the availability of resources like lexicons and corpora, which are still very limited for sentiment analysis research in Chinese language. To this end, we are developing a Chinese common and common sense knowledge base for sentiment analysis by blending the largest existing taxonomy of English common knowledge with a semantic network of English common sense knowledge, and by using machine translation techniques to effectively translate its content into Chinese.

Keywords

AI NLP KR Sentiment Analysis Sentic Computing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Erik Cambria
    • 1
  • Amir Hussain
    • 2
  • Tariq Durrani
    • 3
  • Jiajun Zhang
    • 4
  1. 1.Temasek LaboratoriesNational University of SingaporeSingapore
  2. 2.Dept. of Computing Science and MathematicsUniversity of StirlingUK
  3. 3.Dept. of Electronic and Electrical EngineeringUniversity of StrathclydeUK
  4. 4.National Laboratory of Pattern RecognitionChinese Academy of SciencesChina