[图书][B] Preference-based spatial co-location pattern mining
L Wang, Y Fang, L Zhou - 2022 - Springer
The development of information technology has enabled many different technologies to
collect large amounts of spatial data every day. It is of very great significance to discover …
collect large amounts of spatial data every day. It is of very great significance to discover …
Efficient mining of regional movement patterns in semantic trajectories
Semantic trajectory pattern mining is becoming more and more important with the rapidly
growing volumes of semantically rich trajectory data. Extracting sequential patterns in …
growing volumes of semantically rich trajectory data. Extracting sequential patterns in …
Fraction-score: A new support measure for co-location pattern mining
Co-location patterns are well-established on spatial objects with categorical labels, which
capture the phenomenon that objects with certain labels are often located in close …
capture the phenomenon that objects with certain labels are often located in close …
Parallel grid-based colocation mining algorithms on GPUs for big spatial event data
Colocation patterns refer to subsets of spatial features whose instances are frequently
located together. Mining colocation patterns is important in many applications such as …
located together. Mining colocation patterns is important in many applications such as …
Representative co-location pattern post-mining based on maximal row instances representation model
P Wu, L Wang, P Yang, X Hu - Knowledge-Based Systems, 2024 - Elsevier
The mining result set of spatial prevalent co-location patterns (SPCPs) is often large and
redundant, especially when the prevalence threshold is set to low or long SPCPs are …
redundant, especially when the prevalence threshold is set to low or long SPCPs are …
Efficient discovery of co-location patterns from massive spatial datasets with or without rare features
P Yang, L Wang, X Wang, L Zhou - Knowledge and Information Systems, 2021 - Springer
A co-location pattern indicates a group of spatial features whose instances are frequently
located together in proximate geographic area. Spatial co-location pattern mining (SCPM) is …
located together in proximate geographic area. Spatial co-location pattern mining (SCPM) is …
Grid-based colocation mining algorithms on gpu for big spatial event data: A summary of results
This paper investigates the colocation pattern mining problem for big spatial event data.
Colocation patterns refer to subsets of spatial features whose instances are frequently …
Colocation patterns refer to subsets of spatial features whose instances are frequently …
Fraction-Score: A Generalized Support Measure for Weighted and Maximal Co-location Pattern Mining
Co-location patterns, which capture the phenomenon that objects with certain labels are
often located in close geographic proximity, are defined based on a support measure which …
often located in close geographic proximity, are defined based on a support measure which …
Mining co-location patterns with dominant features
Y Fang, L Wang, X Wang, L Zhou - … , Puschino, Russia, October 7-11, 2017 …, 2017 - Springer
The spatial co-location pattern mining discovers the subsets of spatial features which are
located together frequently in geography. Most of the studies in this field use prevalence to …
located together frequently in geography. Most of the studies in this field use prevalence to …
TSRS: trip service recommended system based on summarized co-location patterns
P Yang, T Zhang, L Wang - Web and Big Data: Second International Joint …, 2018 - Springer
Co-location patterns, whose instances are frequently located together, are particularly
valuable for many applications. With co-location patterns, the location-based service …
valuable for many applications. With co-location patterns, the location-based service …