Mining Order-preserving Submatrices under Data Uncertainty: A Possible-world Approach and Efficient Approximation Methods

Mining Order-preserving Submatrices under Data Uncertainty: A Possible-world Approach and Efficient Approximation Methods

Given a data matrix , a submatrix of is an order-preserving submatrix (OPSM) if there is a permutation of the columns of , under which the entry values of each row in are strictly increasing. OPSM mining is widely used in real-life applications such as identifying coexpressed genes and finding custo...

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Bibliographic Details
Main Authors: Cheng, J. (Author), Hao, X. (Author), Long, C. (Author), Ng, W. (Author), Qu, W. (Author), Wang, X. (Author), Yan, D. (Author)
Format: Article
Language:English
Published: Association for Computing Machinery 2022
Subjects:
Data matrix
Data mining
Dynamic programming
Expected support
Matrix algebra
Mining algorithms
Mining order
OPSM
Order-preserving submatrices
Order-preserving submatrix
Poisson distribution
Possible world semantics
Probabilistic frequentness
Probabilistics
Semantics
Value distribution
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