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A Mapping Model to Match Context Sensing Data to Related Sentences

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Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 461)

Abstract

Following current trends in language learning applications, a context-based language generating application was developed to aid learners in effective language acquisition. In an effort to not only match the user’s situation with a relevant sentence, but also combine context information to create heterogeneous sentences, a new data model was devised. This paper describes the structure of this model based on a sensing data classifier as well as the corresponding language database. It also depicts a usage scenario with a procedural description of the underlying processes.

Keywords

  • Context awareness
  • Context-based learning
  • Experiential awareness
  • Mobile phone sensing
  • Ubiquitous learning

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Acknowledgment

This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. R7120-17-1007, SIAT CCTV Cloud Platform).

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Correspondence to Young-ho Park .

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Surridge, L., Park, Yh. (2018). A Mapping Model to Match Context Sensing Data to Related Sentences. In: Lee, W., Choi, W., Jung, S., Song, M. (eds) Proceedings of the 7th International Conference on Emerging Databases. Lecture Notes in Electrical Engineering, vol 461. Springer, Singapore. https://doi.org/10.1007/978-981-10-6520-0_13

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  • DOI: https://doi.org/10.1007/978-981-10-6520-0_13

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