The Method for Extracting Meaningful Patterns Over the Time of Multi Blocks Stream Data


KIPS Transactions on Computer and Communication Systems, Vol. 3, No. 10, pp. 377-382, Oct. 2014
10.3745/KTCCS.2014.3.10.377,   PDF Download:

Abstract

Analysis techniques of the data over time from the mobile environment and IoT, is mainly used for extracting patterns from the collected data, to find meaningful information. However, analytical methods existing, is based to be analyzed in a state where the data collection is complete, to reflect changes in time series data associated with the passage of time is difficult. In this paper, we introduce a method for analyzing multi-block streaming data(AM-MBSD: Analysis Method for Multi-Block Stream Data) for the analysis of the data stream with multiple properties, such as variability of pattern and large capacitive and continuity of data. The multi-block streaming data, define a plurality of blocks of data to be continuously generated, each block, by using the analysis method of the proposed method of analysis to extract meaningful patterns. The patterns that are extracted, generation time, frequency, were collected and consideration of such errors. Through analysis experiments using time series data.


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Cite this article
[IEEE Style]
K. R. Cho and K. Y. Kim, "The Method for Extracting Meaningful Patterns Over the Time of Multi Blocks Stream Data," KIPS Transactions on Computer and Communication Systems, vol. 3, no. 10, pp. 377-382, 2014. DOI: 10.3745/KTCCS.2014.3.10.377.

[ACM Style]
Kyeong Rae Cho and Ki Young Kim. 2014. The Method for Extracting Meaningful Patterns Over the Time of Multi Blocks Stream Data. KIPS Transactions on Computer and Communication Systems, 3, 10, (2014), 377-382. DOI: 10.3745/KTCCS.2014.3.10.377.