Can I read Classification Non Supervis\'ee Des Donn\'ees H\'et\'erog\`enes \`a Large \'Echelle on EtoBox?

Classification Non Supervis\'ee Des Donn\'ees H\'et\'erog\`enes \`a Large \'Echelle by Zoghlami, Mohamed Ali; Arfaoui, Olfa; Hidri, Minyar Sassi; Ayed, Rahma Ben is a scholarly article available to read on EtoBox.

What is Classification Non Supervis\'ee Des Donn\'ees H\'et\'erog\`enes \`a Large \'Echelle about?

When it comes to cluster massive data, response time, disk access and quality of formed classes becoming major issues for companies. It is in this context that we have come to define a clustering framework for large scale heterogeneous data that contributes to the resolution of these issues. The proposed framework is based on, firstly, the descriptive analysis based on MCA, and secondly, the MapReduce paradigm in a large scale environment. The results are encouraging and prove the efficiency of the hybrid deployment on response quality and time component as on qualitative and quantitative data.

Author

Zoghlami, Mohamed Ali; Arfaoui, Olfa; Hidri, Minyar Sassi; Ayed, Rahma Ben

Published

2017

Language

EN