A Dynamic Bayesian Network Approach to Location Prediction in Ubiquitous Computing Environments

@inproceedings{Lee2010ADB,
  title={A Dynamic Bayesian Network Approach to Location Prediction in Ubiquitous Computing Environments},
  author={Sunyoung Lee and Kun Chang Lee and Heeryon Cho},
  booktitle={International Conference on Advances in Information Technology},
  year={2010}
}
The ability to predict the future contexts of users significantly improves service quality and user satisfaction in ubiquitous computing environments. [] Key Result The evaluation result suggests that a dynamic Bayesian network model offers significant predictive power.
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7 Citations
Background Citations
2
Methods Citations
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7 Citations

Contextual location prediction using spatio-temporal clustering

This study/paper aims to propose a methodology that predicts a user’s location on the basis of a user's mobility history, which uses contextual information that can be acquired easily and accurately with the help of common sensors such as GPS.

Next place prediction by understanding mobility patterns

Three combined models using least entropy, highest probability and ensemble are developed using dynamic Bayesian network (DBN) to solve next place prediction problem for mobility data.

Indoor-ALPS: an adaptive indoor location prediction system

Indoor-ALPS is presented, an Adaptive Indoor Location Prediction System that uses temporal-spatial features to create individual daily models for the prediction of when a user will leave their current location (transition time) and the next location she will transition to.

A novel multilayered context awareness technology for internetware evolution

This paper builds a three-layered architecture for Internetware to avoid disorderly context information transmission and utilizes the ontology model language OWL to formalize Internetware context, to form a unified understanding of context information in the whole Internetware system.

Patterns for context-based knowledge fusion in decision support systems

A Person-search System for an Assistive Robot

Experiments show that the HMM-based person-search system is effective at locating a target person considerably faster than an uninformed baseline approach.

Sentient destination prediction

This work evaluates an adapted ontological construct, which it calls context-specific cognitive frame (CSCF), in order to capture the entire experience of a user at a given moment, and shows that this method can be used to provide a flexible, more accurate and therefore more personalized user experience using the example of location prediction.

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