Open AccessResearch and Optimization of Data Classification using K-means Clustering and Affinity Propagation Technique
Author(s) -
P. Varalakshmi,
Jagadish S. Kallimani,
Jagadish S. Kallimani
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.f1011.0486s419
Subject(s) - cluster analysis , computer science , data mining , fetch , affinity propagation , population , fuzzy clustering , machine learning , cure data clustering algorithm , oceanography , geology , demography , sociology
Amongst various social networking platforms available in this digital millennium, Twitter facilitates a huge platform to accomplish analysis on data with respect to trends, events, personalities etc. Twitter facilitates the analysts in fetching essential information of the population based on their likes and preferences. Clustering technique is one of the prominent techniques available to fetch the essential data from the massive data being populated. Several clustering methods are available to achieve the objective of grouping the data. This paper throws light on the performance and efficiency of several algorithms used in determining the trending pulses effectively. The clusters of data obtained after clustering are further subjected to classification based on the topics for real time analysis. This paper discusses the flaws obtained in the classification of the data. The data is again subjected to an optimized classification technique and analyzed against the clusters of data.