Abstract
A real problem use-case represents a challenge. This is usually transformed (reduced) to a model. We expect the model to give a response/solution which is (at least in a degree) acceptable/meets the challenge. Moreover this challenge-response understanding has two levels – both the real world situation and model situation contains challenge side (input, query, problem…) and the response side (output, answer, solution…). We present a formal model of ChRF-Challenge-Response Framework inspired by our previous work on Galois-Tukey connections. Nevertheless, real world reduction to models needs some adaptation of this formal model. In this paper we introduce several examples extending ChRF. We illustrate this using several practical situations mainly in the area of recommender systems. Data of the model situations are motivated by Fagin-Lotem-Naor’s data model with attribute preferences and multicriterial aggregation. In this realm we review our previous work on preferential interpretation of fuzzy sets; implicit behavior in/and online/offline evaluation of recommender systems. We finish with smart extensions of industrial processes. We propose a synthesis of these and formulate some open problems.
This publication was realized with the support of the Slovak Operational Programme Integrated Infrastructure in the frame of the project: Intelligent systems for UAV real-time operation and data processing, code ITMS2014+: 313011V422 and co-financed by the European Regional Development Fund.
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Notes
- 1.
Supported in 1990–91 by Alexander von Humboldt Foundation, Germany.
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- 4.
IPR source codes: https://github.com/lpeska/Implicit-Preference-Relations, for more resources see the paper.
- 5.
See https://github.com/lpeska/FUZZ-IEEE2020 for source codes, evaluation data and complete results are available from.
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Brezani, S., Vojtas, P. (2021). Aggregation for Flexible Challenge Response. In: Andreasen, T., De Tré, G., Kacprzyk, J., Legind Larsen, H., Bordogna, G., Zadrożny, S. (eds) Flexible Query Answering Systems. FQAS 2021. Lecture Notes in Computer Science(), vol 12871. Springer, Cham. https://doi.org/10.1007/978-3-030-86967-0_16
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