Trace-Based Decision Making in Interactive Application: Case of Tamagotchi systems
Identifieur interne : 000886 ( Main/Exploration ); précédent : 000885; suivant : 000887Trace-Based Decision Making in Interactive Application: Case of Tamagotchi systems
Auteurs : Hoang Nam Ho [France] ; Mourad Rabah [France] ; Samuel Nowakowski [France] ; Pascal Estraillier [France]Source :
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Abstract
— We present our exploratory work for situation preselecting in interactive applications, assuming that the application is an Interactive Adaptive System based on a sequence of contextualized "situations". Each situation confines activities and interactions related to a common context, resources and system actors. When one situation is completed, the system has to determine which is the best following one. We introduce in this paper a new preselecting method that identifies possible next situations among all available situations. We propose a strategy using Naïve Bayes based on the analysis of the sets of available traces (the past of users). Combining all obtained results, we get a set of situations, called set of alternatives that can be used in any decision algorithm. We demonstrate our approach on a case study based on Tamagotchi game.
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Affiliations:
- France
- Grand Est, Lorraine (région), Nouvelle-Aquitaine, Poitou-Charentes
- La Rochelle, Metz, Nancy
- Université de La Rochelle, Université de Lorraine
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Making</term><term>preselection</term><term>situations</term><term>traces</term><term>— interactive adaptive system</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">— We present our exploratory work for situation preselecting in interactive applications, assuming that the application is an Interactive Adaptive System based on a sequence of contextualized "situations". Each situation confines activities and interactions related to a common context, resources and system actors. When one situation is completed, the system has to determine which is the best following one. We introduce in this paper a new preselecting method that identifies possible next situations among all available situations. We propose a strategy using Naïve Bayes based on the analysis of the sets of available traces (the past of users). Combining all obtained results, we get a set of situations, called set of alternatives that can be used in any decision algorithm. We demonstrate our approach on a case study based on Tamagotchi game.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Grand Est</li><li>Lorraine (région)</li><li>Nouvelle-Aquitaine</li><li>Poitou-Charentes</li></region><settlement><li>La Rochelle</li><li>Metz</li><li>Nancy</li></settlement><orgName><li>Université de La Rochelle</li><li>Université de Lorraine</li></orgName></list><tree><country name="France"><region name="Nouvelle-Aquitaine"><name sortKey="Ho, Hoang Nam" sort="Ho, Hoang Nam" uniqKey="Ho H" first="Hoang Nam" last="Ho">Hoang Nam Ho</name></region><name sortKey="Estraillier, Pascal" sort="Estraillier, Pascal" uniqKey="Estraillier P" first="Pascal" last="Estraillier">Pascal Estraillier</name><name sortKey="Nowakowski, Samuel" sort="Nowakowski, Samuel" uniqKey="Nowakowski S" first="Samuel" last="Nowakowski">Samuel Nowakowski</name><name sortKey="Rabah, Mourad" sort="Rabah, Mourad" uniqKey="Rabah M" first="Mourad" last="Rabah">Mourad Rabah</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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