International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Since Year 2012 | Open Access | Double Blind Reviewed

ISSN: 2319-7064




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Survey Paper | Computer Science & Engineering | India | Volume 4 Issue 1, January 2015


Survey of Mining Order-Preserving Submatrices from Data with Repeated Measurements

Swati Gaikwad [2]


Abstract: There some situations, where relative magnitude of data items have more importance than their accurate values. In those situations, Order-preserving submatrices (OPSMs) are proving to be successful in detecting concurrent patterns in data. For example relative magnitudes have importance in the process of analyzing gene expressions profiles which are extracted from microarray experiments. There are two reasons for it 1. Relative magnitudes describe changes in gene activities among whole experiment.2. In these situations, accurate values cannot be trusted since high level of noise is present. As data noise generating problems, Number of experiments has been carried out for collecting multiple measurements to address this issue. An advanced model of OPSM can be experimented and studied in which set of values obtained from replicated experiments are used to represent each data item. New problem can be called OPSM-RM (OPSM with Repeated Measurements). Depending on number of practical requirements, OPSM-RM can be characterized. Generic mining algorithm can be implemented by studying challenges of OPSM-RM.


Keywords: Order-preserving submatrices, Data noise, Relative Magnitude, Data Mining and its methods and algorithm


Edition: Volume 4 Issue 1, January 2015,


Pages: 723 - 725


How to Cite this Article?

Swati Gaikwad, "Survey of Mining Order-Preserving Submatrices from Data with Repeated Measurements", International Journal of Science and Research (IJSR), Volume 4 Issue 1, January 2015, pp. 723-725, https://www.ijsr.net/get_abstract.php?paper_id=SUB15292

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