Mining Popular Patterns: A Novel Mining Problem and Its Application to Static Transactional Databases and Dynamic Data Streams

被引：6

作者：

Cuzzocrea, Alfredo ^{[1
,2
]}

Jiang, Fan ^{[3
]}

Leung, Carson K. ^{[3
]}

Liu, Dacheng ^{[3
,4
]}

Peddle, Aaron ^{[3
]}

Tanbeer, Syed K. ^{[3
]}

机构：

[1] CNR, ICAR, I-87036 Arcavacata Di Rende, CS, Italy

[2] Univ Calabria, I-87036 Arcavacata Di Rende, CS, Italy

[3] Univ Manitoba, Winnipeg, MB, Canada

[4] Wuhan Univ, Wuhan 430072, Hubei, Peoples R China

来源：

TRANSACTIONS ON LARGE-SCALE DATA- AND KNOWLEDGE-CENTERED SYSTEMS XXI | 2015年 / 9260卷

关键词：

Data mining; Knowledge discovery; Interesting patterns; Popular patterns; Useful patterns; Tree-based mining; Data streams;

D O I：

10.1007/978-3-662-47804-2_6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Since the introduction of the frequent pattern mining problem, researchers have extended frequent patterns to different useful patterns such as cyclic, emerging, periodic and regular patterns. In this paper, we (i) introduce popular patterns, which capture the popularity of individuals, items, or events among their peers or groups. Moreover, we also propose (ii) the Pop-tree structure to capture the essential information from transactional databases and (iii) the Pop-growth algorithm formining popular patterns from the Pop-tree. Moreover, we illustrate how our algorithm (iv) mines popular friends from social networks. As we are not confined to mining popular patterns from static transactional databases, we extend our work to mining popular patterns from dynamic data streams. Specifically, we propose (v) the Pop-stream structure to capture the popular patterns in batches of data streams and (vi) the Pop-streaming algorithm for mining popular patterns from the Pop-stream structure. Experimental results showed that (i) our proposed tree structure is compact and space efficient and (ii) our proposed algorithm is time efficient in mining popular patterns from static transactional databases and dynamic data streams.

引用

页码：115 / 139

页数：25

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