A personal knowledge management metamodel based on semantic analysis and social information

Abstract

This article describes the development of a functional architecture for personal knowledge management (PKM), defined from the lessons-learnt concept registered in a mass-use social network analyzed with an algorithm of machine learning. This functional architecture applies, in practical manner, the implementation of a registry system of the personal lessons learnt in the cloud through a Facebook social network. The process starts by acquiring data from the connection to a non-relational database (NoSql) in Amazon’s SimpleDB and to which a complementary analysis algorithm of machine learning has been configured for the semantic analysis of the information registered from lessons learnt and, thus, to study the generation of organizational knowledge management from PKM. The result is the design of a functional architecture that permits integrating the Web 2.0 application and a semantic analysis algorithm from unstructured information by applying machine learning techniques.