Translations as additional contexts for sentence classification

Reinald Kim Amplayo, Kyungjae Lee, Jinyeong Yeo, Seung Won Hwang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)


In sentence classification tasks, additional contexts, such as the neighboring sentences, may improve the accuracy of the classifier. However, such contexts are domain-dependent and thus cannot be used for another classification task with an inappropriate domain. In contrast, we propose the use of translated sentences as domain-free context that is always available regardless of the domain. We find that naive feature expansion of translations gains only marginal improvements and may decrease the performance of the classifier, due to possible inaccurate translations thus producing noisy sentence vectors. To this end, we present multiple context fixing attachment (MCFA), a series of modules attached to multiple sentence vectors to fix the noise in the vectors using the other sentence vectors as context. We show that our method performs competitively compared to previous models, achieving best classification performance on multiple data sets. We are the first to use translations as domainfree contexts for sentence classification.

Original languageEnglish
Title of host publicationProceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018
EditorsJerome Lang
PublisherInternational Joint Conferences on Artificial Intelligence
Number of pages7
ISBN (Electronic)9780999241127
Publication statusPublished - 2018
Event27th International Joint Conference on Artificial Intelligence, IJCAI 2018 - Stockholm, Sweden
Duration: 2018 Jul 132018 Jul 19

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823


Other27th International Joint Conference on Artificial Intelligence, IJCAI 2018

Bibliographical note

Funding Information:
This work was supported by Microsoft Research Asia and the ICT R&D program of MSIT/IITP. [2017-0-01778, Development of Explainable Human-level Deep Machine Learning Inference Framework]

Publisher Copyright:
© 2018 International Joint Conferences on Artificial Intelligence. All right reserved.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence


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