An Online-Offline Combined Big Data Mining Platform
Machine learning libraries are integral to a big data mining platform. There are three limitations on adopting current machine learning libraries in such a platform. First, these algorithms are not implemented for handling both online and offline big data analysis. Second, libraries exist in a variety of frameworks using different programming languages, which make it difficult in integrating several algorithms. Third, most machine learning libraries provides APIs for programming only, thus not user-friendly for those do not have a sufficient understanding of algorithms and those lack of programming skills. In this paper, we implement a comprehensive machine learning library including common algorithms and deep learning algorithms. We integrate this library at a platform level that allows both online and offline data analysis using this library. We further design a user-friendly portal that enables quick and agile data analysis practices. All of these form an Online-Offline Combined Big Data Mining Platform (OOBDP). We present a demonstration of big oil data analysis using this platform. We observe the that OOBDP can easily accommodate industrial requirement for adaptable data mining process, with personalized usage scenarios, and easy to use experiences.