Wireless Network Health Information Retrieval Method Based on Data Mining Algorithm
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초록
In order to improve the low accuracy of traditional wireless network health information retrieval methods, awireless network health information retrieval method is designed based on data mining algorithm. The invalidhealth information stored in wireless network is filtered by data mapping, and the health information is clusteredby data mining algorithm. On this basis, the high-frequency words of health information are classified to realizewireless network health information retrieval. The experimental results show that exactitude of design way issignificantly higher than that of the traditional method, which can solve the problem of low accuracy of thetraditional wireless network health information retrieval method.
Abstract
In order to improve the low accuracy of traditional wireless network health information retrieval methods, awireless network health information retrieval method is designed based on data mining algorithm. The invalidhealth information stored in wireless network is filtered by data mapping, and the health information is clusteredby data mining algorithm. On this basis, the high-frequency words of health information are classified to realizewireless network health information retrieval. The experimental results show that exactitude of design way issignificantly higher than that of the traditional method, which can solve the problem of low accuracy of thetraditional wireless network health information retrieval method.
참고문헌 (21)
- B. J. Elliott, "A content analysis of the health information provided in women's weekly magazines", Health Libraries Review, 11(2), pp.96~103 (1994)
- Mohamed Abdelkrim Senouci, "Flow", Interface Association for multi-connectivity in heterogeneous wireless networks: e-Health case, 2019, pp.94, 101942~[DOI]
- Y. K. Ever, "Secure-anonymous user authentication scheme for e-healthcare application using wireless medical sensor networks", IEEE Systems Journal, 13(1), pp.456~467 (2019)
- X. Zuo, "Power information network intrusion detection based on data mining algorithm", The Journal of Supercomputing, 76(7), pp.5521~5539 (2020)
- M. A. Hossain, "A novel framework for recommending data mining algorithm in dynamic IoT environment", IEEE Access, 8, pp.157333~157345 (2020)
- C. Fiarni, "Analysis and prediction of diabetes complication disease using data mining algorithm", Procedia Computer Science, 161, pp.449~457 (2019)
- David A. Wood, "Net ecosystem carbon exchange prediction and insightful data mining with an optimized data-matching algorithm", Ecological Indicators, 124, pp.107426~ (2021), Elsevier BV[DOI]
- X. Shen, "A combined algorithm for cleaning abnormal data of wind turbine power curve based on change point grouping algorithm and quartile algorithm", IEEE Transactions on Sustainable Energy, 10(1), pp.46~54 (2019)
- A. G. Regino, "Link maintenance for integrity in linked open data evolution : literature survey and open challenges", Semantic Web, 12(3), pp.517~541 (2021)
- Sun Xingrong, "Research on time series data mining algorithm based on Bayesian node incremental decision tree", Cluster Computing, 22(S4), pp.10361~10370 (2017), Springer Science and Business Media LLC[DOI]
- Tamil Selvi M, "Adaptive Lemuria: A progressive future crop prediction algorithm using data mining", Sustainable Computing: Informatics and Systems, 31, pp.100577~ (2021), Elsevier BV[DOI]
- J. K. Sarmah, "A comparative study on use of data mining algorithm in EDM development", IOSR Journal of Computer Engineering, 23(1), pp.44~48 (2021)
- Y. V. Khivintsev, "Spin waves in YIG-based networks : logic and signal processing", Physics of Metals and Metallography, 120, pp.1318~1324 (2019)
- K. Peng, "A deep belief network based health indicator construction and remaining useful life prediction using improved particle filter", Neurocomputing, 361, pp.19~28 (2019)
- P. Santos, "The Metis project—education for health: a project report", Universal Access in the Information Society, 20(2), pp.417~420 (2021)
- L. Abualigah, "A novel feature selection method for data mining tasks using hybrid sine cosine algorithm and genetic algorithm", Cluster Computing, 24, pp.2161~2176 (2021)
- M. Subramaniam, "Modified firefly algorithm and fuzzy c-mean clustering based semantic information retrieval", Journal of Web Engineering, 20(1), pp.33~52 (2021)
- Frederico Damasceno Bortoloti, "Supervised kernel density estimation K-means", Expert Systems with Applications, 168, pp.114350~ (2021), Elsevier BV[DOI]
- Paul J. Messino, "A method for measuring the effect of certified electronic health record technology on childhood immunization status scores among Medicaid managed care network providers", Journal of Biomedical Informatics, 110, pp.103567~ (2020), Elsevier BV[DOI]
- S. Grossberg, "Studies of Mind and Brain", pp.65~156 (1982), Springer
- Z. Qian, "Data mining algorithm based on feature weighting", Journal of Computational Methods in Sciences and Engineering, 19(S1), pp.269~276 (2019)