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Maximum-expectation integrated agglomerative nesting data mining model for cultural datasets

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Abstract

Cultural geo-information system (CGIS) database is mainly used to identify the location and date archeological objects in cultural data analysis. When using various data mining approaches during cultural data analysis in CGIS systems, cohesion and time complexity are considered as one of the major parameters which minimize the quality of patterns or objects in CGIS system. In the recent past, several researchers have looked for ways to minimize cohesion and time complexity caused in the area of CGIS, whereas in research maximum-expectation (MAX-EXP) integrated agglomerative nesting (MAX-EXP-AN) data mining model in the present system to address this issues which helps to minimize the cohesion present in the cluster using distance metrics. The time-complexity in identifying cultural objects in various geo-locations and dates of archeological objects effectively reduced using an optimized pairwise distance measurements technique with less cohesion and error. Furthermore, the experimental validation shows promising results with less errors, cohesion, and time complexity keeps the MAX-EXP-AN suitable for CGIS.

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Funding

The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through Research Group No. RG-1440-078.

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  1. Computer Science Department, Community College, King Saud University, Riyadh, 11437, Saudi Arabia

    Abdulaziz Alarifi & Ayed Alwadain

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  1. Abdulaziz Alarifi
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  2. Ayed Alwadain
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Correspondence to Abdulaziz Alarifi.

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Alarifi, A., Alwadain, A. Maximum-expectation integrated agglomerative nesting data mining model for cultural datasets. Pers Ubiquit Comput 24, 45–55 (2020). https://doi.org/10.1007/s00779-019-01257-6

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  • DOI: https://doi.org/10.1007/s00779-019-01257-6

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