Une approche de fouille de textes pour l’identification automatique de relations spatiales

International audienceLa découverte de connaissances à partir de textes, en particulier l’identification d’informations spatiales, est une tâche difficile due à la complexité destextes écrits en langage naturel. Dans nos travaux, nous proposons une méthode combinant deux approches statistiques (analyse lexicale et contextuelle) et une approche de fouille de textes pour identifier les types de relations spatiales

A survey on diagnosis of diabetes using various classification algorithm

Diabetes is worldwide problem. It occurs when pancreas does not produce sufficient insulin, or body can not sufficiently use insulin it produces. Diabetes person has increase blood glucose in the body. People with diabetes may develop serious problems such as heart disease, stroke, kidney failure, blindness, and premature death. WHO reported, in 2013 it was found that over 382 million people throughout the world had diabetes and mostly occurred in women than men due to improper food habit or low quality of food. Early diagnosis of diabetes is an important challenge. This survey present various classification are used for diagnosis of diabetes such as artificial neural network, support vector machine, naïve bayes, decision tree. PIMA Indian dataset are chosen for diagnosis of diabetes. The research hopes to propose a quicker and more efficient technique of diagnosing the disease, leading to timely treatment of the patients