Semantic Analysis of Tags to Renovate Folksonomies in Social Tagging System
J. Annie Jeba Dafney, A. Lourdes Mary · 2014
Abstract- Grouping resources into set of classes allows easy access to the resources we use in our day-to-day lives. This classification makes the search faster and easier. The process of classifying the resources manually becomes expensive. This cost effectiveness switch to automated classification of resources which depends on the content of the data. This paper deals with the semantic analysis of tags. Collaborative tagging system allows any user to annotate the web resources. The user annotations can be useful to discover the aboutness of resources and also helps to ascertain classification. The social tagging system focuses on using support vector machine (SVM) as a state-of-the-art classification algorithm. We have two large scale social tagging data sets to interpret the characteristics of social classification. This System supports user defined annotations which immensely renovate folksonomies.