Improving transfer learning in cross lingual opinion analysis through negative transfer detection

Lin Gui, Qin Lu, Ruifeng Xu, Qikang Wei, Yuhui Cao

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)


Transfer learning has been used as a machine learning method to make good use of available language resources for other resource-scarce languages. However, the cumulative class noise during iterations of transfer learning can lead to negative transfer which can adversely affect performance when more training data is used. In this paper, we propose a novel transfer learning method which can detect negative transfers. This approach detects high quality samples after certain iterations to identify class noise in new transferred training samples and remove them to reduce misclassifications. With the ability to detect bad training samples and remove them, our method can make full use of large unlabeled training data available in the target language. Furthermore, the most important contribution in this paper is the theory of class noise detection. Our new class noise detection method overcame the theoretic flaw of a previous method based on Gaussian distribution. We applied this transfer learning method with negative transfer detection to cross lingual opinion analysis. Evaluation on the NLP&CC 2013 cross-lingual opinion analysis dataset shows that the proposed approach outperforms the state-of-the-art systems.
Original languageEnglish
Title of host publicationKnowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783319251585
Publication statusPublished - 1 Jan 2015
Event8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015 - Chongqing, China
Duration: 28 Oct 201530 Oct 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015


  • Class noise detection
  • Negative transfer
  • Transfer learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this