Nowadays data is created, shared, and stored at an impressive pace, as the world became more connected, networked, and traceable. In particular, data rapidly increased its scope and size, with the continuous growth in volume, variety, and velocity. Furthermore, data changed from static, complete, and centralized to dynamic, incomplete, and distributed, leading to new challenges undertaken by the field of Big Data Analysis. Consequently, there is the need for novel computational techniques and tools able to assist humans in extracting useful information (knowledge) from the growing volumes of data. Knowledge Discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful and meaningful patterns from such data, and is currently widespread in numerous fields, including science, engineering, healthcare, business, and medicine. A major aspect of Knowledge Discovery is to extract valuable knowledge and information from data.
User Name : Jackson
Posted 17-03-2017 on 16:18:17 AEDT