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• W2895886772 abstract "Spatiotemporal data mining refers to the extraction of knowledge, regularly repeating relationships, and interesting patterns from data with spatial and temporal aspects. In recent years, many spatiotemporal frequent pattern mining algorithms were developed for spatiotemporal event instances represented by a series of region objects that evolves over time. These algorithms focus on the discovery of spatiotemporal co-occurrence patterns and event sequences by inspecting the spatiotemporal overlap and follow relationships. Before moving onto these relationships, we will demonstrate different types of spatiotemporal knowledge to place the relationships and methods in the greater context. This chapter provides a bird-eye view on the output of spatiotemporal data mining techniques in the literature, gives rationale for mining spatiotemporal patterns from evolving regions, and explains the challenges of mining patterns from evolving region data." @default.
• W2895886772 created "2018-10-26" @default.
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• W2895886772 date "2018-01-01" @default.
• W2895886772 modified "2023-09-27" @default.
• W2895886772 title "A Gentle Introduction to Spatiotemporal Data Mining" @default.
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• W2895886772 doi "https://doi.org/10.1007/978-3-319-99873-2_1" @default.
• W2895886772 hasPublicationYear "2018" @default.
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