TEXT CLUSTERING BASED ON THE N-GRAMS BY BIO INSPIRED METHOD (IMMUNE SYSTEMS)

In this paper we present the results of unsupervised classification (clustering) of unstructured data in this case the textual data from Reuters 21578 corpus with a new biomimetic approach using immune systems. Before to experiment the immune systems, we digitalized our data: textual documents from...

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Bibliographic Details
Published in:Researchers world - journal of arts science and commerce 2010-10, Vol.1 (1), p.56
Main Authors: Mohamed, Hamou Reda, Lehireche, Ahmed, Chaouki, Lokbani Ahmed, Mohamed, Rahmani
Format: Article
Language:English
Subjects:
Genetic algorithms
Methods
Studies
Online Access:Get full text
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Summary:In this paper we present the results of unsupervised classification (clustering) of unstructured data in this case the textual data from Reuters 21578 corpus with a new biomimetic approach using immune systems. Before to experiment the immune systems, we digitalized our data: textual documents from the database REUTERS 21,578 corpus by the approach of N-grams. The novelty lies on the hybridization of the n-grams and immune systems for classification. Section 1 gives an introduction and state of the art, Section 2 presents representation of texts based on the n grams, Section 3 describes the approach of immune systems for clustering, Section 4 shows the experimentation and comparison results and finally Section 5 gives a conclusion and perspectives. [PUBLICATION ABSTRACT]
ISSN:2229-4686