FIU-Miner: a fast, integrated, and user-friendly system for data mining in distributed environment

Authors:
Chunqiu Zeng;Yexi Jiang;Li Zheng;Jingxuan Li;Lei Li;Hongtai Li;Chao Shen;Wubai Zhou;Tao Li;Bing Duan;Ming Lei;Pengnian Wang
Affiliations:
Florida International University, Miami, Florida, USA;Florida International University, Miami, Florida, USA;Florida International University, Miami, Florida, USA;Florida International University, Miami, Florida, USA;Florida International University, Miami, Florida, USA;Florida International University, Miami, Florida, USA;Florida International University, Miami, Florida, USA;Florida International University, Miami, Florida, USA;Florida International University, Miami, Florida, USA;ChangHong COC Display Devices Co.,Ltd, Mianyang, China;ChangHong COC Display Devices Co.,Ltd, Mianyang, China;ChangHong COC Display Devices Co.,Ltd, Mianyang, China
Venue:
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Year:
2013

Citing 7
Cited 0

Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy

IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to Data Mining, (First Edition)

Introduction to Data Mining, (First Edition)
Computational Methods of Feature Selection (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)

Computational Methods of Feature Selection (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)
The WEKA data mining software: an update

ACM SIGKDD Explorations Newsletter
Mahout in Action

Mahout in Action
Model mining for robust feature selection

Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
BC-PDM: data mining, social network analysis and text mining system based on cloud computing

Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

The advent of Big Data era drives data analysts from different domains to use data mining techniques for data analysis. However, performing data analysis in a specific domain is not trivial; it often requires complex task configuration, onerous integration of algorithms, and efficient execution in distributed environments.Few efforts have been paid on developing effective tools to facilitate data analysts in conducting complex data analysis tasks. In this paper, we design and implement FIU-Miner, a Fast, Integrated, and User-friendly system to ease data analysis. FIU-Miner allows users to rapidly configure a complex data analysis task without writing a single line of code. It also helps users conveniently import and integrate different analysis programs. Further, it significantly balances resource utilization and task execution in heterogeneous environments. A case study of a real-world application demonstrates the efficacy and effectiveness of our proposed system.