On NIS-Apriori Based Data Mining in SQL

被引：7

作者：

Sakai, Hiroshi ^{[1
]}

Liu, Chenxi ^{[1
]}

Zhu, Xiaoxin ^{[2
]}

Nakata, Michinori ^{[3
]}

机构：

[1] Kyushu Inst Technol, Grad Sch Engn, Kitakyushu, Fukuoka 8048550, Japan

[2] Harbin Inst Technol, Grad Sch Engn, Westdazhi St, Harbin, Peoples R China

[3] Josai Int Univ, Fac Management & Informat Sci, Togane, Chiba 2830002, Japan

来源：

ROUGH SETS, (IJCRS 2016) | 2016年 / 9920卷

关键词：

Association rules; NIS-Apriori algorithm; SQL; Prototype; Uncertainty;

D O I：

10.1007/978-3-319-47160-0_47

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We have proposed a framework of Rough Non-deterministic Information Analysis (RNIA) for tables with non-deterministic information, and applied RNIA to analyzing tables with uncertainty. We have also developed the RNIA software tool in Prolog and getRNIA in Python, in addition to these two tools we newly consider the RNIA software tool in SQL for handling large size data sets. This paper reports the current state of the prototype named NIS-Apriori in SQL, which will afford us more convenient environment for data analysis.

引用

页码：514 / 524

页数：11

共 50 条

[1] On Parallelization of the NIS-Apriori Algorithm for Data Mining
Wu, Mao
Sakai, Hiroshi
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS 19TH ANNUAL CONFERENCE, KES-2015, 2015, 60 : 623 - 631
[2] A NIS-Apriori Based Rule Generator in Prolog and Its Functionality for Table Data
Sakai, Hiroshi
Nakata, Michinori
Slezak, Dominik
ROUGH SETS AND KNOWLEDGE TECHNOLOGY, 2011, 6954 : 226 - +
[3] The Completeness of NIS-Apriori Algorithm and a Software Tool getRNIA
Sakai, Hiroshi
Wu, Mao
2014 IIAI 3RD INTERNATIONAL CONFERENCE ON ADVANCED APPLIED INFORMATICS (IIAI-AAI 2014), 2014, : 115 - 121
[4] On Two Apriori-Based Rule Generators: Apriori in Prolog and Apriori in SQL
Sakai, Hiroshi
Shen, Kao-Yi
Nakata, Michinori
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2018, 22 (03) : 394 - 403
[5] NIS-Apriori-based rule generation with three-way decisions and its application system in SQL
Sakai, Hiroshi
Nakata, Michinori
Watada, Junzo
INFORMATION SCIENCES, 2020, 507 (507) : 755 - 771
[6] DM Data Mining Based on Improved Apriori Algorithm
Wang, Yongping
Jin, Yanfeng
Li, Ying
Geng, Keming
INFORMATION COMPUTING AND APPLICATIONS, ICICA 2013, PT II, 2013, 392 : 354 - 363
[7] Medical diagnosis data mining based on improved Apriori algorithm
Ma, D., 1600, Academy Publisher (09):
[8] Improving algorithm Apriori for data mining
Zhang, Zhuo
Zhang, Lu
Zhong, Shao-Chun
Guan, Jiwen
COMPUTATIONAL INTELLIGENCE IN DECISION AND CONTROL, 2008, 1 : 17 - 22
[9] Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data
Maria Luna, Jose
Padillo, Francisco
Pechenizkiy, Mykola
Ventura, Sebastian
IEEE TRANSACTIONS ON CYBERNETICS, 2018, 48 (10) : 2851 - 2865
[10] DATA MINING OF COLLEGE STUDENTS' MENTAL PROBLEMS BASED ON APRIORI ALGORITHM
Huang, Xinyan
PSYCHIATRIA DANUBINA, 2022, 34 : S363 - S364

← 1 2 3 4 5 →