This paper presents a case-study of a knowledge-based recommender system capable to diagnose post-harvest diseases of apples. It describes the process of knowledge elicitation and construction of a Bayesian Network reasoning system as well as its evaluation with three different types of studies involving diseased apples. The ground truth of diseased instances has been established by genome sequencing in a lab. The paper demonstrates the performance differences of knowledge-based reasoning mechanisms due to different users interacting with the system under different conditions and proposes methods for boosting the performance by likelihood evidence learned from the estimated consensus of users' and expert's interactions.

Sottocornola, G., Baric, S., Stella, F., Zanker, M. (2021). Case study on the development of a recommender for apple disease diagnosis with a knowledge-based Bayesian Network. In Joint Workshop of the 3rd Knowledge-Aware and Conversational Recommender Systems and the 5th Recommendation in Complex Environments, KaRS-ComplexRec 2021. CEUR-WS.

Case study on the development of a recommender for apple disease diagnosis with a knowledge-based Bayesian Network

Stella F.;
2021

Abstract

This paper presents a case-study of a knowledge-based recommender system capable to diagnose post-harvest diseases of apples. It describes the process of knowledge elicitation and construction of a Bayesian Network reasoning system as well as its evaluation with three different types of studies involving diseased apples. The ground truth of diseased instances has been established by genome sequencing in a lab. The paper demonstrates the performance differences of knowledge-based reasoning mechanisms due to different users interacting with the system under different conditions and proposes methods for boosting the performance by likelihood evidence learned from the estimated consensus of users' and expert's interactions.
No
paper
Bayesian Network; Case study in agriculture; Knowledge-based recommendation; Likelihood evidence;
English
Joint Workshop of the 3rd Knowledge-Aware and Conversational Recommender Systems and the 5th Recommendation in Complex Environments, KaRS-ComplexRec 2021 - 25 September 2021
Sottocornola, G., Baric, S., Stella, F., Zanker, M. (2021). Case study on the development of a recommender for apple disease diagnosis with a knowledge-based Bayesian Network. In Joint Workshop of the 3rd Knowledge-Aware and Conversational Recommender Systems and the 5th Recommendation in Complex Environments, KaRS-ComplexRec 2021. CEUR-WS.
Sottocornola, G; Baric, S; Stella, F; Zanker, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/370634
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