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

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