In this paper, we present continuous research on data analysis based on our previous work on similarity search problems. PanKNN is a novel technique which explores the meaning of K nearest neighbors from a new perspective, redefines the distances between data points and a given query point Q, and efficiently and effectively select data points which are closest to Q. It can be applied in various data mining fields. In this paper, we applied the Fuzzy concept to improve the performance of PanKNN, targeting the better decision making for the calculation of the distance between a data point and Q. This approach can assist to improve the performance of existing data analysis approaches.
Digital Object Identifier (DOI)
Yong Shi. 2009. Towards solving similarity search problems using fuzzy concept for multi-dimensional data. In Proceedings of the 47th Annual Southeast Regional Conference (ACM-SE 47). ACM, New York, NY, USA, , Article 84 , 3 pages.