Sequence Mining under Multiple Constraints

被引：5

作者：

Bechet, Nicolas ^{[1
]}

Cellier, Peggy ^{[2
]}

Charnois, Thierry ^{[3
]}

Cremilleux, Bruno ^{[4
]}

机构：

[1] Univ Bretagne Sud, IRISA, Campus Tohann, F-56017 Vannes, France

[2] IRISA, INSA Rennes, F-35042 Rennes, France

[3] Univ Paris 13, Sorbonne Paris Cite, LIPN, F-93430 Villetaneuse, France

[4] Univ Caen Basse Normandie, GREYC, F-14032 Caen 5, France

来源：

30TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, VOLS I AND II | 2015年

关键词：

Sequential data mining; constraint-based data mining; pattern discovery; information extraction; natural language processing; PATTERNS;

D O I：

10.1145/2695664.2695889

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, we address the problem of mining sequential patterns under multiple constraints. Unlike classical algorithms, our approach handles various types of constraints which are not only numeric but also symbolic and syntactic. These multiple constraints enable us to express a large scope of knowledge to focus on interesting patterns. We illustrate our approach with the detection of gene rare disease relationships from biomedical texts for the documentation of rare diseases.

引用

页码：908 / 914

页数：7

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