Abstract
As the interest in IoT is increasing, various researches using IoT is being carried out. Research using IoT aims to provide appropriate services by recognizing user’s condition. These researches utilizing IoT includes the function of supporting user’s decision making, but it cannot provide services to user autonomously. In this study, in order to solve existing problems, we improve the accuracy of the decision tree and suggest algorithm offering services to user autonomously. Proposed algorithm consisted of error correction part and limit value processing part. Through the result of experiment, resolve the problems of existing research and show the higher accuracy than the rule-based decision making algorithm.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kang, J., Kim, H., Jun, M.: Market and Technical Trends of internet of things. International Journal of Contents 13, 14–17 (2015)
Perer, C., Georgakopoulos, D.: Context aware computing for the internet of things: A survey. IEEE Communications Surveys & Tutorials 16, 414–454 (2014)
Kim, H.K., Jeong, S., Kang, H.: Identification of Subgroups with Lower Level of Stroke Knowledge Using Decision-tree Analysis. Journal of Korean Academy of Nursing 44, 97–107 (2014)
Jeong, B., Park, D., Jung, E., Kim, J., Choi, J.: Dempster-Shafer Theory based Clinical Decision Support System Using Clinical Knowledge and Rule Induction of Decision Tree. Journal of Korean Institute of Information Technology 11, 85–90 (2013)
Kim, Y., Ryu, J., Song, W., Kim, M.: Fire Probability Prediction Based on Weather Information Using Decision Tree. Journal of KIISE 40, 705–715 (2013)
That ‘Internet of Things’ thing in the real world, things matter more than ideas. http://www.rfidjournal.com/articles/view?4986
Joo, S.-Y., Lim, H.-S., Kang, D.-S.: A Middleware with Efficient Memory Management Technique and Advanced Structure for M2M Network. JKIIT 12, 101–108 (2014)
Joe, W., Jiang, M., Jeong, K.: An M2M/IoT based Smart Data Logger for Environmental Sensor Networks. KIISE Transactions on Computing Practices (KTCP) 20, 1–5 (2014)
Gu, S., Kim, Y.: A Distributed Data Processing Scheme Considering Dynamic Network on IoT Environment. The e-Business Studies 15, 255–271 (2014)
Kwon, S., Park, D., Bang, H., Park, Y.: Real-time and Parallel Semantic Translation Technique for Large-Scale Streaming Sensor Data in an IoT Environment. Journal of KIISE 42, 54–67 (2015)
Kim, J.: An Effective Data Distribution Scheme in Sensor Network for Internet of Things. The Journal of The Korea Institute of Electronic Communication Sciences 10, 769–774 (2015)
Faragher, R.: Understanding the Basis of the Kalman Filter via a Simple and Intuitive Derivation. IEEE Signal Processing Magazine 29, 128–132 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer Science+Business Media Singapore
About this paper
Cite this paper
Han, C., Moon, H., Kim, C. (2015). A Study on the Algorithm Design for Improving the Accuracy of Decision Tree. In: Park, DS., Chao, HC., Jeong, YS., Park, J. (eds) Advances in Computer Science and Ubiquitous Computing. Lecture Notes in Electrical Engineering, vol 373. Springer, Singapore. https://doi.org/10.1007/978-981-10-0281-6_119
Download citation
DOI: https://doi.org/10.1007/978-981-10-0281-6_119
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0280-9
Online ISBN: 978-981-10-0281-6
eBook Packages: Computer ScienceComputer Science (R0)