文章基本信息

标题：Text Clustering Based on the N-Grams by Bio Inspired Method (Immune Systems).
本地全文：下载
作者：Hamou Reda Mohamed (Algeria), Ahmed Lehireche (Algeria), Lokbani Ahmed Chaouki(Algeria) ; Rahmani Mohamed (Algeria)
期刊名称：Researchers World - Journal of Arts Science & Commerce
印刷版ISSN：2229-4686
电子版ISSN：2229-4686
出版年度：2010
卷号：1
期号：1
页码：56-70
出版社：Educational Research Multimedia & Publication
摘要：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.
关键词：Data classification and clustering; immune systems; biomimetic methods; data mining;N-grams.