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
Published in:
Design and Development of a Robotic Arm for Rehabilitation and Training Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Analysis of Recent Maximal Frequent Pattern Mining Approaches

Authors : Gangin Lee, Unil Yun

Published in: Advances in Computer Science and Ubiquitous Computing

Publisher: Springer Singapore

Log in

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

search-config
loading …

Abstract

Since the concept of representative pattern mining was proposed to solve the limitations of traditional frequent pattern mining, a variety of relevant approaches have been developed. As one of the major techniques in representative pattern mining, maximal frequent pattern mining provides users with a smaller number of more meaningful pattern mining results. In this paper, we analyze characteristics of recent maximal frequent pattern mining methods using various concepts and techniques.

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
previous chapter Document Classification Using Word2Vec and Chi-square on Apache Spark
next chapter Design of Noise Information Storage System Using IoT Devices
Literature
1.
Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: 20th International Conference on Very Large Data Bases, pp. 487–499 (1994)
2.
Goparaju, A., Brazier, T., Salem, S.: Mining representative maximal dense cohesive subnetworks. Netw. Model. Anal. Health Inf. Bioinform. 4(1), 29 (2015)CrossRef
3.
Han, J., Pei, J., Yin, Y., Mao, R.: Mining frequent patterns without candidate generation: a frequent-pattern tree approach. Data Mining Knowl. Discov. 8(1), 53–87 (2004)MathSciNetCrossRef
4.
Lee, G., Yun, U., Ryang, H., Kim, D.: Approximate maximal frequent pattern mining with weight conditions and error tolerance. Int. J. Pattern Recogn. Artif. Intell. 30(6), 1650012:1–1650012:42 (2016)CrossRef
5.
Li, H., Zhang, N.: Probabilistic maximal frequent itemset mining over uncertain databases. In: 21st International Conference on Database Systems for Advanced Applications, pp. 149–163 (2016)
6.
Karim, M., Rashid, M., Jeong, B., Choi, H.: Privacy preserving mining maximal frequent patterns in transactional databases. In: 17th International Conference on Database Systems for Advanced Applications, pp. 303–319 (2012)
7.
Necir, H., Drias, H.: A distributed maximal frequent itemset mining with multi agents system on bitmap join indexes selection. Int. J. Inf. Technol. Manage. 14(2/3), 201–214 (2015)
8.
9.
Salem, S., Ozcaglar, C.: MFMS: maximal frequent module set mining from multiple human gene expression data sets. In: 12th International Workshop on Data Mining in Bioinformatics, pp. 51–57 (2013)
10.
Stattner, E., Collard, M.: MAX-FLMin: an approach for mining maximal frequent links and generating semantical structures from social networks. In: 23rd International Conference on Database and Expert Systems Applications, pp. 468–483 (2012)
11.
Yun, U., Lee, G.: Incremental mining of weighted maximal frequent itemsets from dynamic databases. Expert Syst. Appl. 54, 304–327 (2016)CrossRef
12.
Yun, U., Lee, G., Lee, K.: Efficient representative pattern mining based on weight and maximality conditions. Expert Syst. (2016). (in press)
Metadata
Title
Analysis of Recent Maximal Frequent Pattern Mining Approaches
Authors
Gangin Lee
Unil Yun
Copyright Year
2017
Publisher
Springer Singapore
Book
Advances in Computer Science and Ubiquitous Computing

Print ISBN: 978-981-10-3022-2

Electronic ISBN: 978-981-10-3023-9

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-3023-9_135