Clustering plays an important role in many large-scale data analyses providing users with an overall understanding of their data. Nonetheless, clustering is not an easy task due to noisy features and outliers existing in the data, and thus the clustering results obtained from automatic algorithms often do not make clear sense. To remedy this problem, automatic clustering should be complemented ...

The widespread adoption of machine learning (ML) techniques and the extensive expertise required to apply them have led increased interest in automated ML solutions that reduce need for human intervention. One main challenges applying previously unseen problems is algorithm selection – identification high-performing algorithm(s) a given dataset, task, evaluation measure. This study addresses ch...

Due to the rapid development of internet technology, social media and popular research article databases have generated many open text information. This large amount textual information leads 'Big Data'. Textual can be recorded repeatedly about an event or topic on different websites. Text summarization (TS) is emerging field that helps produce summary from a single multiple documents. The redu...