Open Access
Issue |
ITM Web Conf.
Volume 12, 2017
The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|
|
---|---|---|
Article Number | 03046 | |
Number of page(s) | 5 | |
Section | Session 3: Computer | |
DOI | https://doi.org/10.1051/itmconf/20171203046 | |
Published online | 05 September 2017 |
- Jiawei Han. Data mining concepts and techniques [M]. Morgan Kaufmann Publishers,2011-07-25. [Google Scholar]
- J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68–73. [Google Scholar]
- Agrawal R, Strikant R. Fast algorithms for mining association rules. 20[J]. Proc. int. conf. very Large Database Vldb, 1994,23(3):21–30. K. Elissa, “Title of paper if known,” unpublished. [Google Scholar]
- Han J, Kamber M, Pei J. Data mining, southeast Asia edition: Concepts and techniques [M]. Morgan kaufmann, 2006. [Google Scholar]
- Owens J D, Houston M, Luebke D, et al. GPU computing. [Google Scholar]
- Nvidia B. NVIDIA CUDA Programming Guide [J]. 2012. [Google Scholar]
- Bell Jason. Apache Spark [M] Machine Learning: Hands-On for Developers and Technical Professionals. John Wiley & Sons, Inc, 2015:273–314. [Google Scholar]
- Zaharia M, Chowdhury M, Das T, et al. Resilient distributed datasets: a fault-tolerant abstraction for inmemory cluster computing[C] Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation. USENIX Association, 2012:141–146. [Google Scholar]
- J. Guo and Y.-g. Ren, Research on Improved A Priori Algorithm Based on Coding and MapReduce,” in Web Infromation System and Application Conference (WISA), 2013, pp.294–299. [EDP Sciences] [Google Scholar]
- Sacasere A, Omiecinski E, Navathe S B. An Efficient Algorithm for Mining Association Rules in Large Databases [J]. Vidb Journal. 1995:432–444. [Google Scholar]
- Park J S, Chen M S, Yu P S/ Efficient parallel data mining for association rules[C] International Conference on Information and Knowledge Management.ACM, 1995:31–36. [Google Scholar]
- Qiu H, Gu R, Yuan C, et al. YAFIM: A Parallel Frequent Itemset Minging Algorithm with Spark[C] Parallel & Distributed Processing Symposium Workshops. IEEE, 2014:1664–1671. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.