Application of an ant colony algorithm for text indexing
Nadia Lachetar, Halima Bahi · 2011
Every day, the mass of information available to us increases. This information would be irrelevant if our ability to efficiently access did not increase as well. For maximum benefit, we need tools that allow us to search, sort, index, store, and analyze the available data. We also need tools helping us to find in a reasonable time the desired information by performing certain tasks for us. One of the promising areas is the automatic text categorization. Imagine ourselves in the presence of a considerable number of texts, which are more easily accessible if they are organized into categories according to their theme. Of course, one could ask a human to read the texts and classify them manually. This task is hard if done for hundreds, even thousands of texts. So, it seems necessary to have an automated application, which would consist on indexing text databases. In this article, we present our experiments in automated text categorization, where we suggest the use of an ant colony algorithm. A Naive Bayes algorithm is used as a baseline in our tests.