Efficient Longest Streak Discovery in Multidimensional Sequence Data

Wang, Wentao1,2; Tang, Bo1; Zhu, Min2

10.1007/978-3-319-96893-3_13

2018

16113349

1611-3349

WEB AND BIG DATA (APWEB-WAIM 2018), PT II

10988

166-181

Macau, China

GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND

SPRINGER INTERNATIONAL PUBLISHING AG

This paper studies the problem of discovering longest streak in multidimensional sequence dataset. Given a multidimensional sequence dataset, the contextual longest streak is the longest consecutive tuples in a context subspace which match with a specific measure constraint. It has various applications in social network analysis, computational journalism, etc. The challenges of the longest streak discovery problem are (i) huge search space, and (ii) non-monotonicity property of streak lengths. In this paper, we propose a novel computation framework with a suite of optimization techniques for it. Our solutions outperform the baseline solution by two orders of magnitude in both real and synthetic datasets. In addition, we validate the effectiveness of our proposal by a real-world case study.

Computational journalism Multidimensional sequence data

第一

英语

CPCI-S ; EI

Science and Technology Innovation Committee Foundation of Shenzhen[ZDSYS201703031748284]

Computer Science

Computer Science, Information Systems ; Computer Science, Theory & Methods

WOS:000482623700013

20183205674611

Information management

Data Processing and Image Processing:723.2

Web of Science

1.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen Key Lab Computat Intelligence, Shenzhen, Peoples R China
2.Sichuan Univ, Coll Comp Sci, Chengdu, Sichuan, Peoples R China

Wang, Wentao,Tang, Bo,Zhu, Min. Efficient Longest Streak Discovery in Multidimensional Sequence Data[C]. GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND:SPRINGER INTERNATIONAL PUBLISHING AG,2018:166-181.