Large-scale graph database indexing based on T-mixture model and ICA

被引:0
|
作者
Luo, Bin [1 ]
Zheng, Aihua [1 ]
Tang, Jin [1 ]
Zhao, Haifeng [1 ]
机构
[1] Anhui Univ, Key Lab Intelligent Comp & Signal Proc, Hefei 230039, Peoples R China
基金
中国国家自然科学基金;
关键词
D O I
10.1109/ICIG.2007.179
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes an indexing scheme based on t-mixture model and ICA, which is more robust than Gaussian mixture modeling when atypical points (or outliers) exist or the set of data has heavy tail. This indexing scheme combines optimized vector quantizer and probabilistic approximate-based indexing, scheme. Experimental results on large-scale graph database show a notable efficiency improvement with optimistic precision.
引用
收藏
页码:815 / +
页数:3
相关论文
共 50 条
  • [1] Segmentation of Brain MR Images Based on t-mixture Model
    Zhao, Haifeng
    Xu, Xingming
    Chen, Sibao
    Luo, Bin
    [J]. 2009 3RD INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, VOLS 1-11, 2009, : 2247 - 2250
  • [2] Hierarchical indexing scheme for fast search in large-scale image database
    Ye, HJ
    Xu, GY
    [J]. THIRD INTERNATIONAL SYMPOSIUM ON MULTISPECTRAL IMAGE PROCESSING AND PATTERN RECOGNITION, PTS 1 AND 2, 2003, 5286 : 974 - +
  • [3] A Generic Database Indexing Framework for Large-Scale Geographic Knowledge Graphs
    Sun, Yuhan
    Sarwat, Mohamed
    [J]. 26TH ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS (ACM SIGSPATIAL GIS 2018), 2018, : 289 - 298
  • [4] Attention Based Glaucoma Detection: A Large-scale Database and CNN Model
    Li, Liu
    Xu, Mai
    Wang, Xiaofei
    Jiang, Lai
    Liu, Hanruo
    [J]. 2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, : 10563 - 10572
  • [5] A Minimal Rare Substructures-Based Model for Graph Database Indexing
    Azaouzi, Mehdi
    Ben Romdhane, Lotfi
    [J]. INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA 2016), 2017, 557 : 250 - 259
  • [6] Indexing of large-scale multimedia signals
    Wang, Meng
    Gao, Xinbo
    Yang, Yi
    Shan, Caifeng
    [J]. SIGNAL PROCESSING, 2013, 93 (08) : 2109 - 2110
  • [7] A Brain MR Images Segmentation and Bias Correction Model Based on Students t-Mixture Model
    Chen, Yunjie
    Xu, Qing
    Gu, Shenghua
    [J]. COMPUTER VISION, PT I, 2017, 771 : 63 - 76
  • [8] An Empirical Mixture Model for Large-Scale RTT Measurements
    Fontugne, Romain
    Mazel, Johan
    Fukuda, Kensuke
    [J]. 2015 IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (INFOCOM), 2015,
  • [9] MMES: Mixture Model-Based Evolution Strategy for Large-Scale Optimization
    He, Xiaoyu
    Zheng, Zibin
    Zhou, Yuren
    [J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2021, 25 (02) : 320 - 333
  • [10] CNS: Application of Distributed Indexing Based on Large-Scale Graph Data in Legal Protection of Network Personal Information
    Han, Peiqing
    [J]. INTERNATIONAL JOURNAL OF COOPERATIVE INFORMATION SYSTEMS, 2021, 30 (1-4)