Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Mobile Networks and Applications
Published in: Mobile Networks and Applications 2/2018

19-09-2017

Fractal Research on the Edge Blur Threshold Recognition in Big Data Classification

Authors: Jia Wang, Shuai Liu, Houbing Song

Published in: Mobile Networks and Applications | Issue 2/2018

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Research of the edge blur threshold recognition technology in big multimedia data classification has a great significance, which improves the data storage and safety performance. The traditional suspected boundary problem processing method mainly classified data through their features which were large amount, various types, less density of value and high speed of demand processing. That led to the problems such as inaccuracies and great errors. However, the edge blur threshold recognition technology summarized the methods of classifying data and put forward the principle of data classification. It classified the big multimedia data based on the reduction of feature dimensions and on the differences between the selected data. To determine the edge blur threshold, it used the least squares method. Combined with the decision tree method, it finally realized the classification of big multimedia data. The experimental results showed that the improved method has high precision and low recall rate with less time. This means the presented method has a certain advantage when compares with the classical method.
previous article Verifying the Images Authenticity in Cognitive Internet of Things (CIoT)-Oriented Cyber Physical System
next article Editorial: Machine Learning and Intelligent Wireless Communications (MLICOM 2017)

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Show more products
Literature
1.
Bolón-Canedo V, Sánchez-Maroño N, Alonso-Betanzos A (2014) Data classification using an ensemble of filters[J]. Neurocomputing 135(135):13–20CrossRef
2.
Volpi M, Matasci G, Kanevski M et al (2014) Semi-supervised multiview embedding for hyperspectral data classification[J]. Neurocomputing 145(145):427–437CrossRef
3.
Nguyen TT, Huang JZ, Wu Q et al (2015) Genome-wide association data classification and SNPs selection using two-stage quality-based random forests[J]. BMC Genomics 16(S2):1–11
4.
Shaikh R, Sasikumar M (2015) Data classification for achieving security in cloud computing [J]. Procedia Comput Sci 45:493–498CrossRef
5.
Almuhaideb S, Menai MEB (2014) HColonies: a new hybrid metaheuristic for medical data classification[J]. Appl Intell 41(1):282–298CrossRef
6.
Vahdat A, Morgan J, Mcintyre AR et al (2015) Tapped delay lines for gp streaming data classification with label budgets[C]. In: European conference on genetic programming. Springer International Publishing, Cham, pp 126–138
7.
Carneiro MG, Rosa JL, Lopes AA et al (2014) Network-based data classification: combining K -associated optimal graphs and high-level prediction[J]. J Braz Comput Soc 20(14(1)):1–14MathSciNet
8.
Xu J, Hang R (2014) A new committee-based active learning (CBAL) approach to hyperspectral remote sensing data classification[J]. Remote Sens Lett 5(6):511–520CrossRef
9.
Armanfard N, Reilly JP, Komeili M (2015) Local feature selection for data classification[J]. IEEE Trans Pattern Anal Mach Intell 23(4):1–1
10.
Pitarch Y, Ienco D, Vintrou E et al (2015) Spatio-temporal data classification through multidimensional sequential patterns: application to crop mapping in complex landscape[J]. Eng Appl Artif Intell 37(37):91–102CrossRef
11.
Zhang X, Song Q, Wang G et al (2015) A dissimilarity-based imbalance data classification algorithm[J]. Appl Intell 42(3):544–565CrossRef
12.
Paiva JG, Schwartz W, Pedrini H et al (2015) An approach to supporting incremental visual data classification[J]. IEEE Trans Vis Comput Graph 21(1):4–17CrossRef
13.
D’Addabbo A, Maglietta R (2015) Parallel selective sampling method for imbalanced and large data classification[J]. Pattern Recogn Lett 97(C):61–67CrossRef
14.
Naik B, Nayak J, Behera HS et al (2015) A self adaptive harmony search based functional link higher order ANN for non-linear data classification[J]. Neurocomputing 179(C):69–87
15.
Hiew BY, Tan SC, Lim WS (2016) Intra-specific competitive co-evolutionary artificial neural network for data classification[J]. Neurocomputing 185:220–230CrossRef
16.
Zhou J, Zhu Z, Zhen JI (2014) A memetic algorithm based feature weighting for metabolomics data classification[J]. Chin J Electron 23(4):706–711
17.
Sharma R, Biswas KK (2013) Resolving inconsistency and incompleteness issues in software requirements[M]. Managing requirements knowledge. Springer, Berlin, pp 245–263
18.
Guo S, Guo D, Chen L et al (2016) A centroid-based gene selection method for microarray data classification[J]. J Theor Biol 400:32–41MathSciNetCrossRefMATH
19.
Shaikh RA, Adi K, Logrippo L (2016) A data classification method for inconsistency and incompleteness detection in access control policy sets[J]. Int J Inf Secur 93(10):1–23
20.
Ulutagay G (2015) Suzan Kantarci †. An extension of fuzzy L-R data classification with fuzzy OWA distance[J]. Int J Intell Syst 30(9):1006–1020CrossRef
21.
Xu H, Fan L, Gao X (2015) Projection twin SMMs for 2d image data classification[J]. Neural Comput & Applic 26(1):91–100CrossRef
22.
Duan K, Zhang H, Wang JY (2015) Joint learning of cross-modal classifier and factor analysis for multimedia data classification[J]. Neural Comput & Applic 27(2):1–10
23.
Taheri S, Mammadov M (2015) Structure learning of Bayesian networks using global optimization with applications in data classification[J]. Optim Lett 9(5):931–948MathSciNetCrossRefMATH
24.
Kim T, Chung BD, Lee JS (2016) Incorporating receiver operating characteristics into naive Bayes for unbalanced data classification[J]. Computing:1–16
25.
Yang R, Wang Z (2015) Cross-oriented choquet integrals and their applications on data classification[J]. J Intell Fuzzy Syst 28(1):205–216MathSciNetMATH
26.
Cordero R, Suemitsu WI, Pinto JOP (2015) Analysis and convergence theorem of complex quadratic form as decision boundary for data classification[J]. Electron Lett 51(7):561–562CrossRef
27.
Morales Morales C, Flores U, Adam Medina M et al (2015) Digital artificial neural network implementation on a FPGA for data classification[J]. IEEE Lat Am Trans 13(10):3216–3220CrossRef
28.
Pham VN, Long TN, Pedrycz W (2016) Interval-valued fuzzy set approach to fuzzy co-clustering for data classification[J]. Knowl-Based Syst 107:1–13CrossRef
29.
Gerla V, Murgas M, Radisavljevic VD et al (2014) 25. Incremental learning in the task of eeg data classification[J]. Clin Neurophysiol 125(5):e32–e33CrossRef
30.
Talat E (2014) Advances of swarm intelligent Systems in Gene Expression Data Classification[J]. J Mult Valued Logic Soft Comput 22(3):307–315
31.
Zhang Y, Chen M, Huang D et al (2017) iDoctor: personalized and professionalized medical recommendations based on hybrid matrix factorization[J]. Futur Gener Comput Syst 66:30–35CrossRef
32.
Zhang Y (2016) Grorec: a group-centric intelligent recommender system integrating social, mobile and big data technologie [J]. IEEE Trans Serv Comput 9(5):786–795CrossRef
33.
Zhang Y, Qiu M, Tsai CW et al (2017) Health-CPS: healthcare cyber-physical system assisted by cloud and big data[J]. IEEE Syst J 11(1):88–95CrossRef
34.
Zhang Y, Chen M, Mao S et al (2014) CAP: crowd activity prediction based on big data analysis[J]. IEEE Netw 28(4):52–57CrossRef
35.
Liu Q, Ma Y, Alhussein M et al (2016) Green data center with IoT sensing and cloud-assisted smart temperature controlling system. Comput Netw 101:104–112CrossRef
Metadata
Title
Fractal Research on the Edge Blur Threshold Recognition in Big Data Classification
Authors
Jia Wang
Shuai Liu
Houbing Song
Publication date
19-09-2017
Publisher
Springer US
Published in
Mobile Networks and Applications / Issue 2/2018
Print ISSN: 1383-469X
Electronic ISSN: 1572-8153
DOI
https://doi.org/10.1007/s11036-017-0926-6

Other articles of this Issue 2/2018

Mobile Networks and Applications 2/2018 Go to the issue

OriginalPaper

Large Scale Measurement and Analytics on Social Groups of Device-to-Device Sharing in Mobile Social Networks

EditorialNotes

Editorial: Intelligent Industrial IoT Integration with Cognitive Computing

OriginalPaper

Botanical Internet of Things: Toward Smart Indoor Farming by Connecting People, Plant, Data and Clouds

OriginalPaper

Verifying the Images Authenticity in Cognitive Internet of Things (CIoT)-Oriented Cyber Physical System

OriginalPaper

Non-uniform de-Scattering and de-Blurring of Underwater Images

OriginalPaper

Routing Algorithm with Virtual Topology Toward to Huge Numbers of LEO Mobile Satellite Network Based on SDN