A Biomimetic Approach Based on Immune Systems for Classification of Unstructured Data

TL;DR

This paper introduces a novel hybrid biomimetic method combining n-grams and immune system principles for effective clustering of unstructured textual data, demonstrated on Reuters corpus with promising results.

Contribution

It presents a new hybrid approach integrating n-grams and immune system concepts for text clustering, which is a novel contribution in biomimetic data analysis.

Findings

Effective clustering of Reuters textual data achieved

Hybrid method shows promising results

Potential to solve text clustering problems

Abstract

In this paper we present the results of unstructured data clustering in this case a textual data from Reuters 21578 corpus with a new biomimetic approach using immune system. Before experimenting our immune system, we digitalized textual data by the n-grams approach. The novelty lies on hybridization of n-grams and immune systems for clustering. The experimental results show that the recommended ideas are promising and prove that this method can solve the text clustering problem.