ApproxMAP: Approximate Mining of Consensus Sequential Patterns

  title={ApproxMAP: Approximate Mining of Consensus Sequential Patterns},
  author={Hye-Chung Kum and Jian Pei and Wei Wang and Dean Duncan},
Sequential pattern mining is an important data mining task with broad applications. However, conventional methods may meet inherent difficulties in mining databases with long sequences and noise. They may generate a huge number of short and trivial patterns but fail to find interesting patterns approximately shared by many sequences. To attack these problems, in this paper, we propose the theme of approximate sequential pattern mining roughly defined as identifying patterns approximately shared… CONTINUE READING
Highly Cited
This paper has 108 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 66 extracted citations

Markov Models in the Analysis of Frequent Patterns in Financial Data

Informatica, Lith. Acad. Sci. • 2013
View 4 Excerpts
Highly Influenced

Sequential pattern mining - approaches and algorithms

ACM Comput. Surv. • 2013
View 6 Excerpts
Highly Influenced

Evolving Sequential Patterns Mining Model over Click Stream with Levenshtein-Automata

2008 3rd International Conference on Innovative Computing Information and Control • 2008
View 4 Excerpts
Highly Influenced

Relative similarity and stability in FCA pattern structures using game theory

2017 2nd International Conference on Communication Systems, Computing and IT Applications (CSCITA) • 2017
View 3 Excerpts
Highly Influenced

Extraction de motifs séquentiels. Problèmes et méthodes

Ingénierie des Systèmes d'Information • 2004
View 3 Excerpts
Highly Influenced

108 Citations

Citations per Year
Semantic Scholar estimates that this publication has 108 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…