Generating Training Dataset of Machine Learning Model for Context-Awareness in a Health Status Notification Service


KIPS Transactions on Software and Data Engineering, Vol. 9, No. 1, pp. 25-32, Jan. 2020
https://doi.org/10.3745/KTSDE.2020.9.1.25, Full Text:
Keywords: context-awareness, Machine Learning Model, Generating Training Dataset, Maintaining Accuracy
Abstract

In the context-aware system, rule-based AI technology has been used in the abstraction process for getting context information. However, the rules are complicated by the diversification of user requirements for the service and also data usage is increased. Therefore, there are some technical limitations to maintain rule-based models and to process unstructured data. To overcome these limitations, many studies have applied machine learning techniques to Context-aware systems. In order to utilize this machine learning-based model in the context-aware system, a management process of periodically injecting training data is required. In the previous study on the machine learning based context awareness system, a series of management processes such as the generation and provision of learning data for operating several machine learning models were considered, but the method was limited to the applied system. In this paper, we propose a training data generating method of a machine learning model to extend the machine learning based context-aware system. The proposed method define the training data generating model that can reflect the requirements of the machine learning models and generate the training data for each machine learning model. In the experiment, the training data generating model is defined based on the training data generating schema of the cardiac status analysis model for older in health status notification service, and the training data is generated by applying the model defined in the real environment of the software. In addition, it shows the process of comparing the accuracy by learning the training data generated in the machine learning model, and applied to verify the validity of the generated learning data.


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Cite this article
[IEEE Style]
J. H. Mun, J. S. Choi and J. Y. Choi, "Generating Training Dataset of Machine Learning Model for Context-Awareness in a Health Status Notification Service," KIPS Transactions on Software and Data Engineering, vol. 9, no. 1, pp. 25-32, 2020. DOI: https://doi.org/10.3745/KTSDE.2020.9.1.25.

[ACM Style]
Jong Hyeok Mun, Jong Sun Choi, and Jae Young Choi. 2020. Generating Training Dataset of Machine Learning Model for Context-Awareness in a Health Status Notification Service. KIPS Transactions on Software and Data Engineering, 9, 1, (2020), 25-32. DOI: https://doi.org/10.3745/KTSDE.2020.9.1.25.