NDLI: A Parallel Implementation of Idea Graph to Extract Rare Chances from Big Data

Content Provider	IEEE Xplore Digital Library
Author	Wang, Qinyong Wang, Hao Zhang, Chen Wang, Wei Chen, Zhe Xu, Fanjiang
Copyright Year	2014
Abstract	In current days, data tend to become much bigger than before, and the distributed computing system is an prevalent option to deal with them. As one of powerful tools, MapReduce framework provides a cheap and efficient way to write parallel programs to run on distributed computing systems. Chance discovery (CD) is an extension of data mining, where chance refers to rare but important events or situations. Idea Graph is an efficient algorithm proposed to detect chances. However, the traditional implementation of Idea Graph is sequential, and its performance encounters some bottlenecks when dealing with big data. In this paper, we propose a parallel implementation of Idea Graph using MapReduce to better meet with the challenge of big data. First, we introduce the MapReduce framework, and then Idea Graph is introduced in brief. After that, we present the details on how we design the parallel Idea Graph implementation. In the end of the paper, several experiments are conducted to evaluate the proposed implementation. The experimental results demonstrate the validation of the proposed implementation and its better performance as compared with that of sequential Idea Graph implementation when handling big data.
Starting Page	503
Ending Page	510
File Size	238346
Page Count	8
File Format	PDF
e-ISBN	9781479942749
DOI	10.1109/ICDMW.2014.91
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis IdeaGraph Distributed databases Clustering algorithms Big Data Nickel Big data Distributed Computing Data mining Chance Discovery MapReduce
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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