A novel fuzzy association rule for efficient data mining of ubiquitous real-time data
- PDF / 1,834,914 Bytes
- 11 Pages / 595.276 x 790.866 pts Page_size
- 84 Downloads / 167 Views
ORIGINAL RESEARCH
A novel fuzzy association rule for efficient data mining of ubiquitous real‑time data S. Nagaraj1 · E. Mohanraj2 Received: 6 November 2019 / Accepted: 17 January 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract In ubiquitous stream of data, the issue related to the association rules of fuzzy are considered in this paper, and a new method FFP_USTREAM (Fuzzy Frequent Pattern Ubiquitous Streams) are created. The system of Ubiquitous real-time data incorporates fuzzy ideas with automated streams of data, utilizing the method of sliding window, to mine rules associated for fuzzy logic. The proposed strategy used a matrix of fuzzification where the input patterns related to level of membership to various classes. Attribution of specific classification or class is depending on estimation level of pattern membership. This technique is applied to ten benchmarks data set with classification of learning repository from the UCI machine. The motivation is to evaluate the proposed strategy and, in this manner the performance is compared to a pair of incredible supervised classification algorithms sigmoidal Recurrent Neural Network (RNN) and Adaptive Neuro-fuzzy Inference System (ANFIS). An efficient and complexity of the system are examined. Instances of genuine set of data are utilized to test the proposed system. Existing regression and classification methods is used to compare the proposed fuzzy method. Proposed fuzzy achieves better results when compared to existing method. Keywords Data mining · Fuzzy association rules · Data streams · Ubiquitous data streams
1 Introduction Attractive field of data mining pulled numerous scientists and experts in the industry of information and in inquire research institutes in general in the most recent decades, because of the accessibility of a enormous data and the quick requirement for altering such information into important data and knowledge. The valuable information assembled is applied in numerous zones, like advertisement overview, client maintenance, creation control, analysis of evolution and science investigation (Gaber et al. 2014; Sampathkumar and Vivekanandan 2019). Late developing applications like organized traffic monitoring, data analysis through sensor network, web snap stream mining, estimating the * S. Nagaraj [email protected] E. Mohanraj [email protected] 1
Anna University, Chennai, Tamil Nadu, India
Department of Computer Science and Engineering, K.S. Rangasamy College of Technology, Tiruchengode, Tamil Nadu, India
2
consumption of power, vibrant tracking of vacillations in stock market, call for considering another sort of data known as stream information, which is consistent, conceivably infinite progression of data, instead of limited, statically accumulated data set. Mining of data streams is the extricating procedure for knowledge structures from consistent with quick data records. This system with data streams scattering, remote and mobile/hand held gadgets aims the requirement for a productive ex
Data Loading...
