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Sequential Pattern Mining Using IDLists
, 2020 Sequential pattern mining is a practical problem whose objective is to discover helpful informative patterns in a stored database such as market transaction databases. It covers many applications in different areas. Recently, a study that improved the runtime for mining patterns was proposed.
Huy Minh Huynh +4 more
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Sequential Pattern Mining: Optimum Maximum Sequential Patterns and Consistent Sequential Patterns
2007 IEEE International Conference on Integration Technology, 2007The concepts of optimal maximum sequential pattern and the consistent sequential pattern are introduced to describe the wholesome characteristics of the sequential pattern mining problems. And a mathematical model and two algorithms are constructed to determine the optimal maximum sequential patterns and the consistent ones.
Xilu Wang, Weili Yao
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Proceedings of the Eleventh International Conference on Data Engineering, 2002
We are given a large database of customer transactions, where each transaction consists of customer-id, transaction time, and the items bought in the transaction. We introduce the problem of mining sequential patterns over such databases. We present three algorithms to solve this problem, and empirically evaluate their performance using synthetic data.
Rakesh Agrawal 0001 +1 more
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We are given a large database of customer transactions, where each transaction consists of customer-id, transaction time, and the items bought in the transaction. We introduce the problem of mining sequential patterns over such databases. We present three algorithms to solve this problem, and empirically evaluate their performance using synthetic data.
Rakesh Agrawal 0001 +1 more
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On a Method of Sequential Pattern Recognition
IEEE Transactions on Computers, 1972In this paper, a multistage linear programming method of pattern recognition is proposed. The usual n-dimensional linear program has been split up into n stages of a one-dimensional linear program in such a way that more and more patterns belonging to two classes A and B are correctly classified as we proceed to higher and higher stages.
A. Som, A. K. Nath
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Mining Compressing Sequential Patterns
Proceedings of the 2012 SIAM International Conference on Data Mining, 2012AbstractPattern mining based on data compression has been successfully applied in many data mining tasks. For itemset data, the Krimp algorithm based on the minimum description length (MDL) principle was shown to be very effective in solving the redundancy issue in descriptive pattern mining.
Lam, Hoang Thanh +3 more
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On Suboptimal Sequential Pattern Recognition
IEEE Transactions on Computers, 1968Abstract—In this note, three suboptimal solutions are obtained for the joint sequential feature selection and pattern classification problem. These solutions allow the comparison of two distinctly different approximations to the optimal procedure. One approximation involves simplifying assumptions on the underlying distribution of features for each ...
Gerald P. Cardillo, King-Sun Fu
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Sequential Pattern Mining with Wildcards
2010 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010Sequential 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 +6 more
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