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Intercultural Collaboration and Support Systems: A Brief History

  • Toru IshidaEmail author
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9862)

Abstract

At the beginning of the new millennium, we proposed the concept of intercultural collaboration where participants with different cultures and languages work together towards shared goals. Because intercultural collaboration is a new area with scarce data, it was necessary to execute parallel experiments in both in real fields as well as in research laboratories. In 2002, we conducted a one-year experiment with Japanese, Chinese, Korean and Malaysian colleagues and students to develop open-source software oriented towards machine translation. From this experiment, we understood the necessity of a language infrastructure on the Internet that could create customized multilingual environments for various situations. In 2006, we launched the Language Grid project to realize a federated operation of servers for language services. Using the Language Grid, we worked with a nongovernmental organization since 2011 to support knowledge communications between agricultural experts in Japan and farmers in Vietnam via their children. We observed that a large community emerged to utilize these nonmature machine translation technologies. During these experiences, by facing different types of difficulties, we gradually came to understand the nature of intercultural collaboration. Problems are wicked and not easily defined because of their nested and open networked origin. Fortunately, multiagent technologies can be applied to model and simulate intercultural collaboration so as to predict the difficulties and to prepare a better support systems. In this paper, we provide a brief history of the research and practice as regards intercultural collaboration and support systems.

Keywords

Machine Translation Service Composition Nongovernmental Organization Language Resource Atomic Service 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgments

This work could not have been conducted without the collaboration of a number of colleagues and students. The work was partially supported by a Grant-in-Aid for Scientific Research (S) (24220002, 2012–2016) from Japan Society for the Promotion of Science (JSPS).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Social InformaticsKyoto UniversityKyotoJapan

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