Scalable, Reliable and Robust Data Mining Infrastructures
| Title | Scalable, Reliable and Robust Data Mining Infrastructures |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Pawar, Shrikant, Stanam, Aditya |
| Conference Name | 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4) |
| Date Published | July 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-6823-4 |
| Keywords | data mining, Data visualization, infrastructure, machine learning, Open Source Software, pubcrawl, Robust, Robustness, Scalability, scalable, Scalable Security, Task Analysis, Techniques, Tools |
| Abstract | Mining of data is used to analyze facts to discover formerly unknown patterns, classifying and grouping the records. There are several crucial scalable statistics mining platforms that have been developed in latest years. RapidMiner is a famous open source software which can be used for advanced analytics, Weka and Orange are important tools of machine learning for classifying patterns with techniques of clustering and regression, whilst Knime is often used for facts preprocessing like information extraction, transformation and loading. This article encapsulates the most important and robust platforms. |
| URL | https://ieeexplore.ieee.org/document/9210388 |
| DOI | 10.1109/WorldS450073.2020.9210388 |
| Citation Key | pawar_scalable_2020 |