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Belief propagation through provenance graphs

Belief propagation through provenance graphs
Belief propagation through provenance graphs
Provenance of food describes food, the processes in food transformation, and the food operators from the source to consumption; modelling the history food. In processing food, the risk of contamination increases if food is treated inappropriately. Therefore, identifying critical processes and applying suitable prevention actions are necessary to measure the risk; known as due diligence. To achieve due diligence, food provenance can be used to analyse the risk of contamination in order to find the best place to sample food. Indeed, it supports building rationale over food-related activities because it describes the details about food during its lifetime. However, many food risk models only rely on simulation with little notion of provenance of food. Incorporating the risk model with food provenance through our framework, prFrame, is our first contribution. prFrame uses Belief Propagation (BP) over the provenance graph for automatically measuring the risk of contamination. As BP works efficiently in a factor graph, our next contribution is the conversion of the provenance graph into the factor graph. Finally, an evaluation of the accuracy of the inference by BP is our last contribution.
provenance graph, food provenance, belief propagation, risk model, prFrame, sum-product algorithm, inference, factor graph
145-157
Springer
Batlajery, Belfrit, Victor
2ab3069d-8734-4ba0-9846-ec0ef8cdb897
Weal, Mark
e8fd30a6-c060-41c5-b388-ca52c81032a4
Chapman, Adriane
721b7321-8904-4be2-9b01-876c430743f1
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
Balhajjame, K.
Gehani, A.
Alper, P.
Batlajery, Belfrit, Victor
2ab3069d-8734-4ba0-9846-ec0ef8cdb897
Weal, Mark
e8fd30a6-c060-41c5-b388-ca52c81032a4
Chapman, Adriane
721b7321-8904-4be2-9b01-876c430743f1
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
Balhajjame, K.
Gehani, A.
Alper, P.

Batlajery, Belfrit, Victor, Weal, Mark, Chapman, Adriane and Moreau, Luc (2018) Belief propagation through provenance graphs. Balhajjame, K., Gehani, A. and Alper, P. (eds.) In Provenance and Annotation of Data and Processes: IPAW 2018. vol. 11017, Springer. pp. 145-157 . (doi:10.1007/978-3-319-98379-0_11).

Record type: Conference or Workshop Item (Paper)

Abstract

Provenance of food describes food, the processes in food transformation, and the food operators from the source to consumption; modelling the history food. In processing food, the risk of contamination increases if food is treated inappropriately. Therefore, identifying critical processes and applying suitable prevention actions are necessary to measure the risk; known as due diligence. To achieve due diligence, food provenance can be used to analyse the risk of contamination in order to find the best place to sample food. Indeed, it supports building rationale over food-related activities because it describes the details about food during its lifetime. However, many food risk models only rely on simulation with little notion of provenance of food. Incorporating the risk model with food provenance through our framework, prFrame, is our first contribution. prFrame uses Belief Propagation (BP) over the provenance graph for automatically measuring the risk of contamination. As BP works efficiently in a factor graph, our next contribution is the conversion of the provenance graph into the factor graph. Finally, an evaluation of the accuracy of the inference by BP is our last contribution.

Text
IPAW2018_2_CameraReady_Black (002) - Accepted Manuscript
Restricted to Repository staff only until 6 September 2019.
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More information

Accepted/In Press date: 13 May 2018
e-pub ahead of print date: 6 September 2018
Venue - Dates: Provenance Week '18: 7th International Provenance And Annotation Workshop, London, United Kingdom, 2018-07-09 - 2018-07-13
Keywords: provenance graph, food provenance, belief propagation, risk model, prFrame, sum-product algorithm, inference, factor graph

Identifiers

Local EPrints ID: 421810
URI: https://eprints.soton.ac.uk/id/eprint/421810
PURE UUID: 2cd24865-fb3e-44b2-9d6f-1fde91e3bd68
ORCID for Belfrit, Victor Batlajery: ORCID iD orcid.org/0000-0001-7637-9481
ORCID for Mark Weal: ORCID iD orcid.org/0000-0001-6251-8786
ORCID for Adriane Chapman: ORCID iD orcid.org/0000-0002-3814-2587
ORCID for Luc Moreau: ORCID iD orcid.org/0000-0002-3494-120X

Catalogue record

Date deposited: 28 Jun 2018 16:30
Last modified: 20 Jul 2019 01:21

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