Discovery of Sequential Event Patterns based on Interestingness

DOI Web Site
  • Sakurai Shigeaki
    Corporate Research & Development Center, Toshiba Corporation
  • Ueno Ken
    Corporate Research & Development Center, Toshiba Corporation
  • Suyama Akihiro
    Corporate Research & Development Center, Toshiba Corporation
  • Orihara Ryohei
    Corporate Research & Development Center, Toshiba Corporation

Bibliographic Information

Other Title
  • 興味度に基づいた時系列イベントパターンの発見
  • キョウミド ニ モトズイタ ジケイレツ イベントパターン ノ ハッケン

Search this article

Abstract

Sequential pattern mining methods efficiently discover all frequent sequential patterns by using apriori property. However, analysts are not always interested in frequent patterns, because the patterns are common and the analysts cannot get new knowledge from the patterns. The paper proposes a new criterion which discovers interesting patterns for the analysts. The paper shows that the criterion satisfies the apriori property and how the criterion is related to existing criteria: support and confidence. Also, the paper proposes an efficient sequential pattern mining method based on the proposed criterion. Moreover, the paper shows its effect by applying it to daily business reports given from a sales force automation system.

Journal

Keywords

Details 詳細情報について

Report a problem

Back to top