This paper reports about a possible approach to integrating a recommendation system (RS) for giving support to users during the creation of Internet of Things (IoT) personalization rules on the Block Composer tailoring environment. Recommending for end-user creation of rules requires a specific way to model the problem different from a user-item matrix filling approach. The items to be recommended (trigger-action rules) are not unitary objects but are composed of several parts, assembled in a step-bystep process. This feature makes recommendations for this end-user development (EUD) approach similar to the sequence-based recommender systems and can be exploited to provide more suitable suggestions.

Recommendations for personalization rules in block composer

Mattioli A.;Paterno' F.
2020

Abstract

This paper reports about a possible approach to integrating a recommendation system (RS) for giving support to users during the creation of Internet of Things (IoT) personalization rules on the Block Composer tailoring environment. Recommending for end-user creation of rules requires a specific way to model the problem different from a user-item matrix filling approach. The items to be recommended (trigger-action rules) are not unitary objects but are composed of several parts, assembled in a step-bystep process. This feature makes recommendations for this end-user development (EUD) approach similar to the sequence-based recommender systems and can be exploited to provide more suitable suggestions.
2020
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
Giuseppe Desolda, Vincenzo Deufemia, Cristina Gena, Maristella Matera, Fabio Paternò, Barbara Treccani
Proceedings of the 1st International Workshop on Empowering People in Dealing with Internet of Things Ecosystems co-located with International Conference on Advanced Visual Interfaces (AVI 2020)
EMPATHY 2020 Empowering People in Dealing with Internet of Things Ecosystems
41
44
http://ceur-ws.org/Vol-2702/
Sì, ma tipo non specificato
29/09/2020
Evento online
Recommender systems
Personalization rules
Sequence-based recommendations
2
open
Mattioli, A.; Paterno', F.
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/424104
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