A Survey of Classification Techniques in the Area of Big Data

March 25, 2015 ยท The Cartographer ยท ๐Ÿ› arXiv.org

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: A Survey of Classification Techniques in the Area of Big Data"

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Authors Praful Koturwar, Sheetal Girase, Debajyoti Mukhopadhyay arXiv ID 1503.07477 Category cs.LG: Machine Learning Citations 42 Venue arXiv.org Last Checked 2 days ago
Abstract
Big Data concern large-volume, growing data sets that are complex and have multiple autonomous sources. Earlier technologies were not able to handle storage and processing of huge data thus Big Data concept comes into existence. This is a tedious job for users unstructured data. So, there should be some mechanism which classify unstructured data into organized form which helps user to easily access required data. Classification techniques over big transactional database provide required data to the users from large datasets more simple way. There are two main classification techniques, supervised and unsupervised. In this paper we focused on to study of different supervised classification techniques. Further this paper shows a advantages and limitations.
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