A Biomimetic Approach Based on Immune Systems for Classification of Unstructured Data
This addresses text clustering for unstructured data, but appears incremental as it combines existing techniques (n-grams and immune systems).
The paper tackles unstructured text clustering by proposing a biomimetic approach that hybridizes n-grams and immune systems, tested on the Reuters 21578 corpus, with results described as promising for solving the text clustering problem.
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.