Rough Set Theory Approach for Classifying Multimedia Data

被引：0

作者：

Rahman, M. Nordin A. ^{[1
]}

Lazim, Yuzarimi M. ^{[1
]}

Mohamed, Farham ^{[1
]}

Safei, Suhailan ^{[1
]}

Deris, Sufian Mat ^{[1
]}

Yusof, M. Kamir ^{[1
]}

机构：

[1] Univ Sultan Zainal Abidin, Fac Informat, Kuala Terengganu 21300, Malaysia

来源：

SOFTWARE ENGINEERING AND COMPUTER SYSTEMS, PT 2 | 2011年 / 180卷

关键词：

Rough set theory; multimedia data management; approximation; classification; data clustering;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The huge size of multimedia data requires for efficient data classification and organization in providing effective multimedia data manipulation. Those valuable data must be captured and stored for potential purposes. One of the main problems in Multimedia Information System (MIS) is the management of multimedia data. As a consequence, multimedia data management has emerged as an important research area for querying. retrieving, inserting and updating of these vast multimedia data. This research considers the rough set theory technique to organize and categorize the multimedia data. Rough set theory method is useful for exploring multimedia data and simplicity to construct multimedia data classification. Classification will help to improve the performance of multimedia data retrieving and organizing process.

引用

页码：116 / 124

页数：9

共 50 条

[31] Rough set based attribute reduction approach in data mining
Li, K
Liu, YS
2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS, 2002, : 60 - 63
[32] A rough set approach to the discovery of classification rules in spatial data
Leung, Yee
Fung, Tung
Mi, Ju-Sheng
Wu, Wei-Zhi
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2007, 21 (09) : 1033 - 1058
[33] An Analysis on Deep Learning Approach Performance in Classifying Big Data Set
Mohamad, Masurah
Selamat, Ali
Salleh, Khairulliza Ahmad
2019 1ST INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND DATA SCIENCES (AIDAS2019), 2019, : 35 - 39
[34] Supervaluationism and Rough Set Theory
Fu, Hao Cheng
2012 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING (GRC 2012), 2012,
[35] Rough Set Theory and Digraphs
Chiaselotti, Giampiero
Ciucci, Davide
Gentile, Tommaso
Infusino, Federico
FUNDAMENTA INFORMATICAE, 2017, 153 (04) : 291 - 325
[36] A Group Incremental Approach to Feature Selection Applying Rough Set Technique
Liang, Jiye
Wang, Feng
Dang, Chuangyin
Qian, Yuhua
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2014, 26 (02) : 294 - 308
[37] A hybrid approach of rough set theory and genetic algorithm for fault diagnosis
C.L. Huang
T.S. Li
T.K. Peng
The International Journal of Advanced Manufacturing Technology, 2005, 27 : 119 - 127
[38] A hybrid approach of rough set theory and genetic algorithm for fault diagnosis
Huang, CL
Li, TS
Peng, TK
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2005, 27 (1-2) : 119 - 127
[39] New heuristic method for data discretization based on rough set theory
ZHAO Jun
The Journal of China Universities of Posts and Telecommunications, 2009, 16 (06) : 113 - 120
[40] MMR: An algorithm for clustering categorical data using Rough Set Theory
Parmar, Darshit
Wu, Teresa
Blackhurst, Jennifer
DATA & KNOWLEDGE ENGINEERING, 2007, 63 (03) : 879 - 893

← 1 2 3 4 5 →