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A hash-based index for processing frequent updates and continuous location-based range queries
Wide range of location-based services and sensors in GIS have to manage moving objects that change their position with respect to time. These...
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Frequent Pattern Mining
Frequent pattern mining deals with identifying the common trends and behaviors in datasets. These trends represent information that may not be...
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An improved frequent pattern tree: the child structured frequent pattern tree CSFP-tree
Frequent itemsets are itemsets that occur frequently in a dataset. Frequent itemset mining extracts specific itemsets with supports higher than or...
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Continuous frequent contact detection over moving objects
With the outbreak of COVID-19 pandemic, contact tracing and social distance monitoring have been increasingly popular due to their capability of...
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Enhancing frequent location privacy-preserving strategy based on geo-Indistinguishability
The increasing use of hand-held devices which have access to location information, has raised the risk of privacy disclosure. To implement privacy...
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Hadamard Encoding Based Frequent Itemset Mining under Local Differential Privacy
Local differential privacy (LDP) approaches to collecting sensitive information for frequent itemset mining (FIM) can reliably guarantee privacy....
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An innovative clustering approach utilizing frequent item sets
Clustering is a method in data mining that belongs to the category of unsupervised learning. Cluster analysis categorizes data into different classes...
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Modeling dynamic spatiotemporal user preference for location prediction: a mutually enhanced method
As the cornerstone of location-based services, location prediction aims to predict user’s next location through modeling user’s personal preference...
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A fundamental approach to discover closed periodic-frequent patterns in very large temporal databases
Periodic frequent-pattern mining (PFPM) is a vital knowledge discovery technique that identifies periodically occurring patterns in a temporal...
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Which Way to Go - Finding Frequent Trajectories Through Clustering
Trajectory clustering is one of the most important issues in mobility patterns data mining. It is applied in several cases such as hot-spots...
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Trajectory test-train overlap in next-location prediction datasets
Next-location prediction, consisting of forecasting a user’s location given their historical trajectories, has important implications in several...
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Mining frequent patterns with generalized linear model for traffic density analysis
Call Detail Record (CDR) is the detailed record of all the telephonic calls that pass through a telephone exchange or any other telecommunications...
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Multi-type concept drift detection under a dual-layer variable sliding window in frequent pattern mining with cloud computing
The detection of different types of concept drift has wide applications in the fields of cloud computing and security information detection. Concept...
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Hilbert curves-based location privacy technique for vehicular cloud networks
Location privacy (LP) plays an important role in location-based services (LBS) offered by different service providers. Many applications request...
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Community detection based on improved user interaction degree, weighted quasi-local path-based similarity and frequent pattern mining
Community detection is a significant research area in social networks. Most methods use network topology, but combining it with user interactions...
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Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases
An uncertain geo-referenced transactional database represents the probabilistic data produced by stationary spatial objects observing a particular...
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Location Attention Knowledge Embedding Model for Image-Text Matching
Image-text matching is the core algorithm of cross-modal retrieval, which plays a central role in connecting vision and text. Due to the well-known...
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Frequent itemset mining using FP-tree: a CLA-based approach and its extended application in biodiversity data
The efficient discovery of frequent itemsets from a transaction database is the fundamental step for association rule mining in data analytics....
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A spatially-aware algorithm for location extraction from structured documents
Place names facilitate locating and distinguishing geographic space where human activities and natural phenomena occur. Extracting place names at...
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Evolution inspired binary flower pollination for the uncapacitated facility location problem
The present paper introduces a modified flower pollination algorithm (FPA) enhanced by evolutionary operators to solve the uncapacitated facility...
