Bayesian Modelling of Community-Based Multidimensional Trust in Participatory Sensing under Data Sparsity

Venanzi, Matteo; Teacy, W. T. Luke; Rogers, Alex; Jennings, Nicholas R.

Bayesian Modelling of Community-Based Multidimensional Trust in Participatory Sensing under Data Sparsity

Matteo Venanzi, W. T. Luke Teacy, Alex Rogers, Nicholas R. Jennings

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Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 717-723.

Abstract

We propose a new Bayesian model for reliable aggregation of crowdsourced estimates of real-valued quantities in participatory sensing applications. Existing approaches focus on probabilistic modelling of user's reliability as the key to accurate aggregation. However, these are either limited to estimating discrete quantities, or require a significant number of reports from each user to accurately model their reliability. To mitigate these issues, we adopt a community-based approach, which reduces the data required to reliably aggregate real-valued estimates, by leveraging correlations between the reporting behaviour of users belonging to different communities. As a result, our method is up to 16.6% more accurate than existing state-of-the-art methods and is up to 49% more effective under data sparsity when used to estimate Wi-Fi hotspot locations in a real-world crowdsourcing application.

Matteo Venanzi, W. T. Luke Teacy, Alex Rogers, and Nicholas R. Jennings. 2015. Bayesian Modelling of Community-Based Multidimensional Trust in Participatory Sensing under Data Sparsity. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 717–723. https://ijcai.org/proceedings/2015/107

@inproceedings{ijcai2015p107,
  title     = {Bayesian Modelling of Community-Based Multidimensional Trust in Participatory Sensing under Data Sparsity},
  author    = {Venanzi, Matteo and Teacy, W. T. Luke and Rogers, Alex and Jennings, Nicholas R.},
  booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-15}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Qiang Yang and Michael Wooldridge},
  pages     = {717--723},
  year      = {2015},
  month     = {7},
  note      = {Main Track},
  url       = {https://ijcai.org/proceedings/2015/107},
}

TY  - CPAPER
TI  - Bayesian Modelling of Community-Based Multidimensional Trust in Participatory Sensing under Data Sparsity
AU  - Venanzi, Matteo
AU  - Teacy, W. T. Luke
AU  - Rogers, Alex
AU  - Jennings, Nicholas R.
T2  - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2015
SP  - 717
EP  - 723
UR  - https://ijcai.org/proceedings/2015/107
ER  -