Title: Analysing knowledge in social big data

Authors: Brahim Lejdel

Addresses: University of El-Oued, El-Oued, Algeria

Abstract: Big data has become an important issue for a large number of research areas such as data mining, machine learning, computational intelligence, the semantic web, and social networks. The combination of big data technologies and traditional machine learning algorithms has generated new and interesting challenges in other areas as social media and social networks. These new challenges are focused mainly on problems such as data processing, data storage, data representation and visualising data. In this paper, we will present a new approach that can extract entities and their relationships from social big data, allowing for the inference of new meaningful knowledge. This approach is a hybrid approach of multi-agent systems and K-means algorithm.

Keywords: K-means; multi-agent systems; MASs; big data; data mining; social networks.

DOI: 10.1504/IJCC.2021.120388

International Journal of Cloud Computing, 2021 Vol.10 No.5/6, pp.480 - 491

Received: 21 Jan 2019
Accepted: 03 Nov 2019

Published online: 10 Jan 2022 *

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