Call for Papers
Without data, there is no machine learning (ML), so there is no doubt that big data and ML are inextricably linked. However, much research to date has tended to treat them as separate areas of development. As we are confronted with today’s difficult problems and the wealth of held data continues to grow, it is vital that new, innovative ways of examining, testing, and using big data to produce useful information are both researched/developed and integrated. Whether this be for the social good (health diagnostics, for example) or corporate gain (competitive advantage), given the exponentially increase in both the volume of data and the velocity by which it is generated, the need for the expansion of direct cooperation of mining big data with ML is long overdue. For this Special Issue, as the individual fields of advanced machine learning and advanced data mining are well established, the focus will be specifically on their intersection: the point―or points―at which one aids, needs, or enhances the other.
This new frontier is almost boundless, but will eventually become the norm. Automatically learning and improving from experience without being explicitly programmed gives great opportunities. The quality of the data being used, its speed of acquisition, and the effectiveness of processing are all of vital importance―if Microsoft’s AI chatbot Tay taught us anything at all, it is certainly this.