Semantic HMC for Big Data Analysis

TL;DR

This paper introduces Semantic HMC, a scalable, non-supervised ontology learning approach that enhances big data analysis through semantic hierarchical multi-label classification, combining machine learning and rule-based reasoning.

Contribution

It presents a novel Semantic HMC framework that integrates scalable machine learning with rule-based reasoning for big data analysis, based on non-supervised ontology learning.

Findings

Demonstrates the effectiveness of Semantic HMC in big data contexts.

Shows improved data analysis accuracy with the proposed method.

Provides a scalable approach combining machine learning and reasoning.

Abstract

Analyzing Big Data can help corporations to im-prove their efficiency. In this work we present a new vision to derive Value from Big Data using a Semantic Hierarchical Multi-label Classification called Semantic HMC based in a non-supervised Ontology learning process. We also proposea Semantic HMC process, using scalable Machine-Learning techniques and Rule-based reasoning.