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WIREs Data Mining Knowl Discov
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Context‐aware movement analytics: implications, taxonomy, and design framework

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Movement of an entity is greatly affected by its internal and external contexts. Such consequential influence has created new paradigms for context‐aware movement data mining and analysis. The significance of incorporating contextual information and movement data is becoming quite evident because of the growing interest in context‐aware movement analysis. Despite such importance, there is limited consensus among researchers on the definition of context and context‐aware system design in movement studies. Therefore, this paper comprehensively reviews current concepts of context and provides a definition and a taxonomy for context in movement analysis. The paper proceeds by providing a definition of context‐aware systems in the movement area after a complete review and comparison of the present definitions present in the literature. Inspired by related works, the paper further suggests a holistic three‐layer design framework tailored to context‐aware systems in movement studies to examine in greater depth the techniques applied during the design stages. The paper outlines the challenges and emergent issues in future research directions in context‐aware movement analysis. The present study is an attempt to bridge the gap between solely using context and developing context‐aware systems, thus paving the way for further research in movement applications.

A taxonomy for context in movement studies.
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Modeling context for a recommendation system.
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The layered architecture of the recommendation system.
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Conceptual framework for context‐aware systems in movement studies.
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Fundamental Concepts of Data and Knowledge > Data Concepts
Fundamental Concepts of Data and Knowledge > Human Centricity and User Interaction
Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining

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