Ala Saleh Alluhaidan^1,*, Pushparaj², Anitha Subbappa³, Ved Prakash Mishra⁴, P. V. Chandrika⁵, Anurika Vaish⁶, Sarthak Sengupta⁶

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5821-5836, 2023, DOI:10.32604/cmc.2023.033995

Abstract ESystems based on EHRs (Electronic health records) have been in use for many years and their amplified realizations have been felt recently. They still have been pioneering collections of massive volumes of health data. Duplicate detections involve discovering records referring to the same practical components, indicating tasks, which are generally dependent on several input parameters that experts yield. Record linkage specifies the issue of finding identical records across various data sources. The similarity existing between two records is characterized based on domain-based similarity functions over different features. De-duplication of one dataset or the linkage of multiple data sets has become… More >

Qianqian Li¹, Meng Li², Lei Guo^3,*, Zhen Zhang⁴

Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 199-205, 2020, DOI:10.32604/jihpp.2020.016299

Abstract On-site programming big data refers to the massive data generated in the process of software development with the characteristics of real-time, complexity and high-difficulty for processing. Therefore, data cleaning is essential for on-site programming big data. Duplicate data detection is an important step in data cleaning, which can save storage resources and enhance data consistency. Due to the insufficiency in traditional Sorted Neighborhood Method (SNM) and the difficulty of high-dimensional data detection, an optimized algorithm based on random forests with the dynamic and adaptive window size is proposed. The efficiency of the algorithm can be elevated by improving the method… More >