【检索号】求助查询EIcompendexaccessionnumber检索号各位帮我...
答案:2 悬赏:10 手机版
解决时间 2021-01-31 12:02
- 提问者网友：不要迷恋哥
- 2021-01-31 00:52
【检索号】求助查询EIcompendexaccessionnumber检索号各位帮我...
最佳答案
- 五星知识达人网友：污到你湿
- 2021-01-31 01:42
【答案】 Accession number:
201446195465
Title:
MR-Apriori: Association Rules algorithm based on MapReduce
Authors:
Lin, Xueyan1
Author affiliation: 1 Information School, Ningbo City College of Vocational Technology, Zhejiang Province, China
Corresponding author:
Lin, Xueyan
Source title:
Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
Abbreviated source title:
Proc.IEEE Int. Conf. Software Eng. Serv. Sci., ICSESS
Issue date:
October 21, 2014
Publication year:
2014
Pages:
141-144
Article number:
6933531
Language:
English
ISSN:
23270586
E-ISSN:
23270594
ISBN-13:
9781479932788
Document type:
Conference article (CA)
Conference name:
2014 5th IEEE International Conference on Software Engineering and Service Science, ICSESS 2014
Conference date:
June 27, 2014 - June 29, 2014
Conference location:
Beijing, China
Conference code:
108800
Publisher:
IEEE Computer Society
Abstract:
Traditional Association Rules algorithm has computing power shortage in dealing with massive datasets. In order to overcome these problems, a distributed association rulesalgorithm based on MapReduce programming model named MR-Apriori is proposed. In this paper, we introduce the MapReduce programming model of Hadoop platform and Apriori algorithm of data mining, propose the detailed procedure of MR-Apriori algorithm. Theoretical and experimental results show MR-Apriori algorithm make a sharp increase in efficiency.
Number of references:
5
Main heading:
Association rules
Controlled terms:
Data mining
Uncontrolled terms:
Apriori - Apriori algorithms - Hadoop - Map-reduce
Classification code:
723.3 Database Systems - 903.1 Information Sources and Analysis
DOI: 10.1109/ICSESS.2014.6933531
Database:
Compendex
Compilation and indexing terms, © 2014 Elsevier Inc.
201446195465
Title:
MR-Apriori: Association Rules algorithm based on MapReduce
Authors:
Lin, Xueyan1
Author affiliation: 1 Information School, Ningbo City College of Vocational Technology, Zhejiang Province, China
Corresponding author:
Lin, Xueyan
Source title:
Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
Abbreviated source title:
Proc.IEEE Int. Conf. Software Eng. Serv. Sci., ICSESS
Issue date:
October 21, 2014
Publication year:
2014
Pages:
141-144
Article number:
6933531
Language:
English
ISSN:
23270586
E-ISSN:
23270594
ISBN-13:
9781479932788
Document type:
Conference article (CA)
Conference name:
2014 5th IEEE International Conference on Software Engineering and Service Science, ICSESS 2014
Conference date:
June 27, 2014 - June 29, 2014
Conference location:
Beijing, China
Conference code:
108800
Publisher:
IEEE Computer Society
Abstract:
Traditional Association Rules algorithm has computing power shortage in dealing with massive datasets. In order to overcome these problems, a distributed association rulesalgorithm based on MapReduce programming model named MR-Apriori is proposed. In this paper, we introduce the MapReduce programming model of Hadoop platform and Apriori algorithm of data mining, propose the detailed procedure of MR-Apriori algorithm. Theoretical and experimental results show MR-Apriori algorithm make a sharp increase in efficiency.
Number of references:
5
Main heading:
Association rules
Controlled terms:
Data mining
Uncontrolled terms:
Apriori - Apriori algorithms - Hadoop - Map-reduce
Classification code:
723.3 Database Systems - 903.1 Information Sources and Analysis
DOI: 10.1109/ICSESS.2014.6933531
Database:
Compendex
Compilation and indexing terms, © 2014 Elsevier Inc.
全部回答
- 1楼网友：鸽屿
- 2021-01-31 03:10
和我的回答一样，看来我也对了
我要举报
如以上问答信息为低俗、色情、不良、暴力、侵权、涉及违法等信息，可以点下面链接进行举报！
大家都在看
推荐资讯