Constructing adaptive configuration dialogs using crowd data

Détails

ID Serval
serval:BIB_D5F7550A978C
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
Constructing adaptive configuration dialogs using crowd data
Titre de la conférence
Proceedings of the 29th ACM/IEEE international conference on Automated software engineering - ASE '14
Auteur(s)
Hamidi S., Andritsos P., Liaskos S.
Editeur
ACM
Adresse
Vasteras, Sweden
ISBN
9781450330138
Statut éditorial
Publié
Date de publication
09/2014
Peer-reviewed
Oui
Série
Automated Software Engineering
Pages
485-490
Langue
anglais
Résumé
As modern software systems grow in size and complexity so do their configuration possibilities. Users are easy to be confused and overwhelmed by the amount of choices they need to make in order to fit their systems to their exact needs. We propose a method to construct adaptive configuration elicitation dialogs through utilizing crowd wisdom. A set of configuration preferences in the form of association rules is first mined from a crowd configuration data set. Possible configuration elicitation dialogs are then modeled through a Markov Decision Process (MDP). Association rules are used to inform the model about configuration decisions that can be automatically inferred from knowledge already elicited earlier in the dialog. This way, an MDP solver can search for elicitation strategies which maximize the expected amount of automated decisions, reducing thereby elicitation effort and increasing user confidence of the result. The method is applied to the privacy configuration of Facebook.
Création de la notice
22/08/2017 12:58
Dernière modification de la notice
21/08/2019 5:15
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