Search Space Engine Optimize Search Using FCC_STF Algorithm in Fuzzy Co-Clustering

TL;DR

This paper proposes an FCC_STF algorithm to improve fuzzy co-clustering by addressing outliers and the curse of dimensionality, enhancing search space optimization in web page clustering.

Contribution

Introduction of the FCC_STF algorithm that fuses fuzzifier for better handling of outliers and high-dimensional data in fuzzy co-clustering.

Findings

FCC_STF reduces outlier impact effectively.

FCC_STF outperforms FCCM and FUZZY CO-DOK in experiments.

Optimizes search space in 2-D for web pages.

Abstract

Fuzzy co-clustering can be improved if we handle two main problem first is outlier and second curse of dimensionality .outlier problem can be reduce by implementing page replacement algorithm like FIFO, LRU or priority algorithm in a set of frame of web pages efficiently through a search engine. The web page which has zero priority (outlier) can be represented in separate slot of frame. Whereas curse of dimensionality problem can be improved by implementing FCC_STF algorithm for web pages obtain by search engine that reduce the outlier problem first. The algorithm FCCM and FUZZY CO-DOK are compared with FCC_STF algorithm with merit and demerits on the bases of different fuzzifier used. FCC_STF algorithm in which fuzzifier fused into one entity who have shown high performance by experiment result of values (A1,B1,Vcj,A2,B2) seem to less sensitive to local maxima and obtain optimization search space in 2-D for web pages by plotting graph between J(fcc_stf) and Vcj.