Data Science and Knowledge Discovery

<p>Data Science (DS) is gaining significant importance in the decision process due to a mix of various areas including Computer Science Machine Learning Math and Statistics domain/business knowledge software development and traditional research. In the business field DS's application allows using scientific methods processes algorithms and systems to extract knowledge and insights from structured and unstructured data to support the decision process. After collecting the data it is crucial to discover the knowledge. In this step Knowledge Discovery (KD) tasks are used to create knowledge from structured and unstructured sources (e.g. text data and images). The output needs to be in a readable and interpretable format. It must represent knowledge in a manner that facilitates inferencing. KD is applied in several areas such as education health accounting energy and public administration. This book includes fourteen excellent articles which discuss this trending topic and present innovative solutions to show the importance of Data Science and Knowledge Discovery to researchers managers industry society and other communities. The chapters address several topics like Data mining Deep Learning Data Visualization and Analytics Semantic data Geospatial and Spatio-Temporal Data Data Augmentation and Text Mining.</p>