NDLI: Spatial trajectories segmentation: trends and challenges

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Spatial trajectories segmentation: trends and challenges

Content Provider	ACM Digital Library
Author	Damiani, Maria Luisa
Abstract	Given a sequence S of temporally ordered observations, non necessarily of spatial nature, the segmentation task partitions S in a set of disjoint sub-sequences $s_{i},$ ., $s_{n}$ - the segments - such that ∪i∈[1, n] $s_{i}$ = S. Typically, segments represents sub-sequences that are somehow homogeneous with respect to some criteria. Depending on the context and the nature of observations, segments can be given an approximated representation, for example segments can be assigned a descriptive label or one of the data points is chosen as representative of the whole sub-sequence. The final result is a summarized representation of the sequence. This simple and intuitive mechanism has been extensively studied in literature, for example, for the summarization of time series. Interestingly, the notion of segment is also at the basis of the most recent trajectory data models. For example, segments are the informative units in the semantic trajectories, where they are called episodes. Episodes are spatial sub-trajectories that can be semantically annotated using application-dependent descriptions, e.g. place names [1]. Similarly the recent symbolic trajectory data model [2] describes the individual movement as a sequence of temporally annotated labeled states $s_{1},$ $.s_{n},$ where each state $s_{i}$ is associated with a time interval. Beyond data modeling, segmentation can be employed for the indexing of trajectories in moving object databases while another major role is to support data analysis, especially for the extraction of individual mobility patterns. The concept of trajectory segment is thus emerging as shared and perhaps unifying concept across data modeling, indexing and analysis.
Starting Page	1
Ending Page	1
Page Count	1
File Format	PDF
ISBN	9781450345828
DOI	10.1145/3004725.3007201
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-10-31
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Segmentation Data models Trajectories Mobility pettern
Content Type	Text
Resource Type	Article

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