Large Graph Mining using Big Data Analytics |
Author(s): |
| Bharati K. , Bharati Vidyapeeth College Of Engineering, Kharghar; Kanchan Doke, Bharati Vidyapeeth College Of Engineering, Kharghar |
Keywords: |
| Frequent Itemset Mining, Outliers, Aggregation |
Abstract |
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Data mining represents the process of extracting interesting and previously unknown knowledge (patterns) from data. Nowadays due to high internet usage and huge data generation in large scale organizations, universities or social networks, it is difficult to store, manage and analyze the data and retrieve the useful information. This arose the need for big data analysis on large databases to generate useful inferences leading to organizational growth. The system will perform mining on a graph database using semi structured data to deduce desirable and appropriate results[2]. The potential users of this system may include Business Analysts, Data Analysts, etc. Such a system can be used for applications like transaction processing, social media Analysis, spam filters, or Intrusion Detection Systems. |
Other Details |
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Paper ID: IJSRDV5I21555 Published in: Volume : 5, Issue : 2 Publication Date: 01/05/2017 Page(s): 1640-1643 |
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