Abstract Identifying the trending topics in journals and conferences is valuable for understanding role of authors, institutions, funding agencies progression knowledge produced field. However, many available clustering methods do not accommodate a desire temporally clustered results that are typical trends, part because time publication often neglected as feature. As demonstration how can be e...

In many practical applications, it is crucial to perform automatic data clustering without knowing the number of clusters in advance. The evolutionary computation paradigm good at dealing with this task, but existing algorithms encounter several deficiencies, such as encoding redundancy and cross-dimension learning error. article, we propose a novel elastic differential evolution algorithm solv...