Results 261 to 270 of about 14,528 (304)

Mining Compressed Sequential Patterns

2006
Current sequential pattern mining algorithms often produce a large number of patterns. It is difficult for a user to explore in so many patterns and get a global view of the patterns and the underlying data. In this paper, we examine the problem of how to compress a set of sequential patterns using only K SP-Features(Sequential Pattern Features).
Lei Chang, Dongqing Yang, Shiwei Tang, Tengjiao Wang 0003   +3 more
openaire   +1 more source

Keyphrase Extraction with Sequential Pattern Mining

Proceedings of the AAAI Conference on Artificial Intelligence, 2017
Existing studies show that extracting a complete keyphrase candidate set is the first and crucial step to extract high quality keyphrases from documents. Based on a common sense that words do not repeatedly appear in an effective keyphrase, we propose a novel algorithm named KCSP for document-specific keyphrase candidate search using ...
Qingren Wang, Victor S. Sheng, Xindong Wu 0001   +2 more
openaire   +1 more source

Sequential Pattern Mining in Multiple Streams

Fifth IEEE International Conference on Data Mining (ICDM'05), 2006
In this paper, we deal with mining sequential patterns in multiple data streams. Building on a state-of-the-art sequential pattern mining algorithm PrefixSpan for mining transaction databases, we propose MILE, an efficient algorithm to facilitate the mining process.
Gong Chen, Xindong Wu 0001, Xingquan Zhu 0001   +2 more
openaire   +1 more source

MAIL: mining sequential patterns with wildcards

International Journal of Data Mining and Bioinformatics, 2013
Sequential pattern mining is an important research task in many domains, such as biological science. In this paper, we study the problem of mining frequent patterns from sequences with wildcards. The user can specify the gap constraints with flexibility. Given a subject sequence, a minimal support threshold and a gap constraint, we aim to find frequent
Fei Xie 0002, Xindong Wu 0001, Xuegang Hu, Jun Gao 0006, Dan Guo 0001, Yulian Fei, Ertian Hua   +6 more
openaire   +2 more sources

Sequential pattern mining algorithms review

Intelligent Data Analysis, 2012
From the beginning of sequential pattern mining to the present, this field has received important attention within the data mining area, because it has a wide application in several significant computational problems. Many algorithms have been created and several techniques have been used with the objective of improving the discovery of the frequent ...
José Kadir Febrer-Hernández, José Hernández-Palancar   +1 more
openaire   +1 more source

Sequential Pattern Mining

2014
Sequential pattern mining, which discovers frequent subsequences as patterns in a sequence database, has been a focused theme in data mining research for over a decade. This problem has broad applications, such as mining customer purchase patterns and Web access patterns.
Wei Shen, Jianyong Wang, Jiawei Han
openaire   +1 more source

Parallel mining of closed sequential patterns

Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, 2005
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most useful one since it retains all the information of the complete pattern set but is often much more compact than it.
Shengnan Cong, Jiawei Han 0001, David A. Padua   +2 more
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A New Algorithm for Mining Sequential Patterns

2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008
AprioriAll and AprioriSome are very famous algorithms for mining sequential patterns, which are used to find motifs on a fixed min-support number. In this paper, we contribute a new algorithm that can find all motifs on any min-support numbers.
Zhuo Zhang 0011, Lu Zhang 0012, Shaochun Zhong, Jiwen Guan   +3 more
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Visualizing sequential patterns for text mining

IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings, 2002
A sequential pattern in data mining is a finite series of elements such as A/spl rarr/B/spl rarr/C/spl rarr/D where A, B, C, and D are elements of the same domain. The mining of sequential patterns is designed to find patterns of discrete events that frequently happen in the same arrangement along a timeline. Like association and clustering, the mining
Pak Chung Wong, Wendy Cowley, Harlan Foote, Elizabeth Jurrus, James J. Thomas   +4 more
openaire   +1 more source

Mining and Ranking Generators of Sequential Patterns

Proceedings of the 2008 SIAM International Conference on Data Mining, 2008
Sequential pattern mining ¯rst proposed by Agrawal and Srikant has received intensive research due to its wide range applicability in many real-life domains. Various improvements have been proposed which include mining a closed set of sequential patterns.
LO, David, KHOO, Siau-Cheng, LI, Jinyan
openaire   +1 more source