This paper describes several interpolation methods for predicting the number of cases of the COVID-19 pandemic. The interpolation methods include some well-known temporal interpolation algorithms including Lagrange interpolation, cubic spline ...

Clustering is a fundamental task in unsupervised learning, one that targets to group a dataset into clusters of similar objects. There has been recent interest in embedding normative considerations around fairness within clustering formulations. In this ...

Big data are everywhere nowadays. Many businesses possess big data for their success because big data are very useful and are considered as new oil. For instance, big data are very important in predicting the trends on what will happen in the future. ...

A collection of related files often exhibits strong similarities among its constituents. These similarities, and the dual differences, may be used for both compressing the collection and for organizing it in a manner that reveals human-readable ...

Social networks have been transforming the way people express opinions, post and react to events, and share ideas. Over the last decade, several studies on event detection from social media have been proposed, with the aim of extracting specific types ...