Semantic trajectories modeling and analysis

@article{Parent2013SemanticTM,
  title={Semantic trajectories modeling and analysis},
  author={Christine Parent and Stefano Spaccapietra and Chiara Renso and Gennady L. Andrienko and Natalia V. Andrienko and Vania Bogorny and Maria Luisa Damiani and Aris Gkoulalas-Divanis and Jos{\'e} Ant{\^o}nio Fernandes de Mac{\^e}do and Nikos Pelekis and Yannis Theodoridis and Zhixian Yan},
  journal={ACM Comput. Surv.},
  year={2013},
  volume={45},
  pages={42:1-42:32}
}
Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey… 

Figures from this paper

Modeling, Mining, and Analyzing Semantic Trajectories: The Process to Extract Meaningful Behaviors of Moving Objects
TLDR
This paper study closely the current researches on modeling and mining semantic trajectories so far, and try to investigate by proposing a descriptive schema including all steps that users can browse from the construction of the trajectories to the analyze of behaviors extracted.
Semantic Trajectories: A Survey from Modeling to Application
TLDR
This paper investigates the current studies on semantic trajectories so far and proposes a new classification schema for the research efforts in semantic trajectory construction and applications, including three main classes: semantic trajectory modeling, computation, and applications.
Semantic enrichment and analysis of movement data: probably it is just starting!
TLDR
An overview of proposals and possible developments in semantic enrichment and analysis of movement data is provided and some details of the current methods to associate movement data with concepts and/or instances described in ontologies or Linked Open Data (LOD).
Semantic trajectory analysis for identifying locations of interest of moving objects
  • A. Nishad, Sajimon Abraham
  • Computer Science
    2017 International Conference on Networks & Advances in Computational Technologies (NetACT)
  • 2017
TLDR
This model considers direction of the movement of the object as semantic mean for the identification of interesting locations on the basis of spatio temporal attributes of moving objects and its semantic features.
From Trajectory Modeling to Social Habits and Behaviors Analysis
TLDR
This paper describes considerable recent research works related to the analysis of mobile spatio-temporal data, focusing on the study of social habits and behaviors, and provides a general perspective on studies on human mobility by depicting and comparing methods and algorithms.
Semantic Trajectory Based Behavior Generation for Groups Identification
TLDR
A novel trajectory semantics calculation method to identify groups that have similar behaviors by measuring the similarity between semantic trajectories and a pruning strategy is proposed to lighten tedious calculations and comparisons.
Trajectory pattern mining: Exploring semantic and time information
TLDR
This work proposes two algorithms to discover frequent semantic trajectory patterns, which are referred to as the moving patterns with spatial, temporal, and semantic attributes from the semantic mobility sequence.
Understanding Occupancy Patterns of Stay Locations using Semantic Trajectory Analytics
TLDR
A prototype system is proposed that is built using a data model that has an ability to hold information of moving and changing objects in the context of dynamic built environment to completely understand meanings behind objects` mobility related interactions.
Multiple-aspect analysis of semantic trajectories(MASTER)
TLDR
A formal framework to use stop-and-move sequence expression as a query language for semantic trajectories is proposed using the RDF (Resource Data Framework) formalism combined with SPARQL queries.
Extracting Semantics of Individual Places from Movement Data by Analyzing Temporal Patterns of Visits
TLDR
An intelligent system that learns how to classify personal places and trips while a human analyst visually analyzes and semantically annotates selected subsets of movement data is planned.
...
...

References

SHOWING 1-10 OF 136 REFERENCES
A model for enriching trajectories with semantic geographical information
TLDR
This paper proposes a data preprocessing model to add semantic information to trajectories in order to facilitate trajectory data analysis in different application domains and shows that the query complexity for the semantic analysis of trajectories will be significantly reduced.
Semantic Annotation of GPS Trajectories
TLDR
An extensible trajectory annotation model, which is oriented on the notion of episodes and allows a clear separation of semantic and physical trajectory information is introduced and a program to support trajectory annotation independent of the recorded location is developed.
SeMiTri: a framework for semantic annotation of heterogeneous trajectories
TLDR
This paper presents SeMiTri - the framework that enables annotating trajectories for any kind of moving objects, and has been evaluated using many GPS datasets from multiple sources -- including both fast moving objects and people's trajectories.
ST‐DMQL: A Semantic Trajectory Data Mining Query Language
TLDR
This paper proposes through a semantic trajectory data mining query language several functionalities to select, preprocess, and transform trajectory sample points into semantic trajectories at higher abstraction levels, in order to allow the user to extract meaningful, understandable, and useful patterns from trajectories.
A clustering-based approach for discovering interesting places in trajectories
TLDR
The proposed solution is a spatio-temporal clustering method, based on speed, to work with single trajectories, and it is shown that the computation of stops using the concept of speed can be interesting for several applications.
Trajectory pattern mining
TLDR
This paper develops an extension of the sequential pattern mining paradigm that analyzes the trajectories of moving objects and introduces trajectory patterns as concise descriptions of frequent behaviours in terms of both space and time.
C-safety: a framework for the anonymization of semantic trajectories
TLDR
This method provides an upper bound to the probability of inferring that a given person, observed in a sequence of non-sensitive places, has also visited any sensitive location, and proposes an algorithm for transforming any dataset of semantic trajectories into a c-safe one.
Weka‐STPM: a Software Architecture and Prototype for Semantic Trajectory Data Mining and Visualization
TLDR
This article presents a software architecture for semantic trajectory data mining as well as the first software prototype to enrich trajectory data with both semantic information and data mining, which is interoperable with databases constructed under OGC specifications.
Visually exploring movement data via similarity-based analysis
TLDR
This paper proposes a framework that provides several trajectory similarity measures, based on primitive as well as on derived parameters of trajectories (speed, acceleration, and direction), which quantify the distance between two trajectories and can be exploited for trajectory data mining, including clustering and classification.
...
...