Machine learning algorithms applied in automatic classification of social network users

Author

de Lima, B.V.A. ; Machado, V.P.

Author_Institution

Dept. de Inf. e Estetistica, Lab. de Intel. Computacional, Teresina, Brazil

fYear

2012

fDate

21-23 Nov. 2012

Firstpage

58

Lastpage

62

Abstract

This work shows the results of an analysis of machine learning algorithms applied in automatic classification for the users of the social network called Scientia.Net. The tests were done using a database with 2000 users. The analysis identifies which algorithm performs better in automatic classification of users within a social network. The algorithms tested were Multilayer Perceptron, Support Vector Machine, Kohonen Network and K-means Algorithm.

Keywords

learning (artificial intelligence); multilayer perceptrons; pattern classification; social networking (online); support vector machines; Kohonen network; Scientia.Net; automatic classification; k-means algorithm; machine learning algorithms; multilayer perceptron; social network users; support vector machine; Clustering algorithms; Databases; Error analysis; Machine learning algorithms; Social network services; Support vector machines; Training; Classification; Cluster; Machine Learning; Scientia.Net; profile;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Aspects of Social Networks (CASoN), 2012 Fourth International Conference on

Conference_Location

Sao Carlos

Print_ISBN

978-1-4673-4793-8

Type

conf

DOI

10.1109/CASoN.2012.6412378

Filename

6412378