Matching Attributes Across Overlapping Heterogeneous Data Sources Using Mutual Information

被引：3
作者：
Zhao, Huimin [1 ]
机构：
[1] Univ Wisconsin Milwaukee, Sheldon B Lubar Sch Business, Milwaukee, WI 53201 USA
来源：
JOURNAL OF DATABASE MANAGEMENT | 2010年 / 21卷 / 04期
关键词：
Attribute Correspondence; Attribute Matching; Heterogeneous Databases; Information Theory; Mutual Information; SEMANTIC-INTEGRATION; SCHEMA; CORRESPONDENCES; RETRIEVAL; DATABASES;
D O I：
10.4018/jdm.2010100105
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Identifying matching attributes across heterogeneous data sources is a critical and time-consuming step in integrating the data sources. In this paper, the author proposes a method for matching the most frequently encountered types of attributes across overlapping heterogeneous data sources. The author uses mutual information as a unified measure of dependence on various types of attributes. An example is used to demonstrate the utility of the proposed method, which is useful in developing practical attribute matching tools.
引用
收藏
页码：91 / 110
页数：20
相关论文
共 48 条
  • [31] Data-Driven Estimation Of Mutual Information Using Frequency Domain and its Application to Epilepsy
    Malladi, Rakesh
    Johnson, Don H.
    Kalamangalam, Giridhar P.
    Tandon, Nitin
    Aazhang, Behnaam
    2017 FIFTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, 2017, : 2015 - 2019
  • [32] Automatic georeferencing of airborne pushbroom scanner images with missing ancillary data using mutual information
    Cariou, Claude
    Chehdi, Kacem
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2008, 46 (05): : 1290 - 1300
  • [33] Rejecting deep brain stimulation artefacts from MEG data using ICA and mutual information
    Abbasi, Omid
    Hirschmann, Jan
    Schmitz, Georg
    Schnitzler, Alfons
    Butz, Markus
    JOURNAL OF NEUROSCIENCE METHODS, 2016, 268 : 131 - 141
  • [34] Inference of single-cell network using mutual information for scRNA-seq data analysis
    Chang, Lan-Yun
    Hao, Ting-Yi
    Wang, Wei-Jie
    Lin, Chun-Yu
    BMC BIOINFORMATICS, 2024, 25 (SUPPL 2):
  • [35] Modified mutual information feature selection algorithm to predict COVID-19 using clinical data
    Rayan, R. Ame
    Suruliandi, A.
    Raja, S. P.
    COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING, 2024,
  • [36] Semantic Web-Based Small Sample Data Recommendation Algorithm Using Weighted Mutual Information
    Liu, Lifeng
    Xu, Qinan
    Zhao, Xuxia
    Cheng, Ping
    INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS, 2025, 21 (01)
  • [37] Two-Stage Hybrid Gene Selection Using Mutual Information and Genetic Algorithm for Cancer Data Classification
    Rani, M. Jansi
    Devaraj, D.
    JOURNAL OF MEDICAL SYSTEMS, 2019, 43 (08)
  • [38] Shoreline extraction from the fusion of LiDAR DEM data and aerial images using mutual information and genetic algrithms
    Yousef, Amr
    Iftekharuddin, Khan
    PROCEEDINGS OF THE 2014 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2014, : 1007 - 1014
  • [39] Gene Expression Data Classification using Support Vector Machine and Mutual Information-based Gene Selection
    Vanitha, Devi Arockia C.
    Devaraj, D.
    Venkatesulu, M.
    GRAPH ALGORITHMS, HIGH PERFORMANCE IMPLEMENTATIONS AND ITS APPLICATIONS (ICGHIA 2014), 2015, 47 : 13 - 21
  • [40] Two-Stage Hybrid Gene Selection Using Mutual Information and Genetic Algorithm for Cancer Data Classification
    M. Jansi Rani
    D. Devaraj
    Journal of Medical Systems, 2019, 43
12345