State of the Art Construction Based on the J48 Classifier: Case Study of Internet of Things

Abstract

Abstract. The bibliometric technics allow us to illustrate aspects of interpretation of data obtained through data bases that are focus in science spreading, which offers an aggregated value to researchers. In this article, we explore the importance of such obtained information from articles' query; in this particular case study the Internet of Things (IoT). The obtained and preprocessed metadata is used to feed the decision tree classification (J48) algorythms, as a result of the training stage, we generated a decision tree/classification where the subjects of research are visualized within a four year time frame. The construction of this classification tree is based in entropy, thus, the order or disorder in which the subjects of research can be interpreted within a level of relevancy in the time frame mentioned. We conceived the visualization and interpretation as the state of the art for the subjects addressed for a particular case, which help researchers to infer tendencies within specific subjects of research.