This repository hosts the materials for a seminar paper developed as part of the Novel advances in Data Science course at KIT. The paper focuses on the challenges and solutions in detecting correlation among time-series data streams, with particular emphasis on both global and local correlation types. It introduces efficient methods for real-time processing of time-series data, addressing the limitations of traditional approaches when dealing with large volumes of data streams.
For a detailed presentation of the seminar, please visit the following link: Seminar Presentation.