Εμφάνιση απλής εγγραφής

dc.contributor.author Osche, P.-E en
dc.contributor.author Castagnos, Sylvain en
dc.contributor.author Boyer, Anne en
dc.date.accessioned 2019-04-07T08:01:41Z
dc.date.available 2019-04-07T08:01:41Z
dc.date.issued 2019-04-07
dc.identifier.uri http://hdl.handle.net/11400/20263
dc.rights Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.title From Music to Museum: Applications of Multi-Objective Ant Colony Systems to Real World Problems en
heal.type conferenceItem
heal.language en
heal.access free
heal.publicationDate 2019
heal.bibliographicCitation Pierre-Edouard Osche, Sylvain Castagnos, Anne Boyer (2019), "From Music to Museum: Applications of Multi-Objective Ant Colony Systems to Real World Problems", 11th Workshop on Adaptive and Learning Agents (ALA 2019), in conjunction with the ACM International Conference on Autonomous Agents and Multiagent Systems AAMAS 2019. Montreal, Canada, May, 2019 en
heal.abstract Recommender systems are a flourishing domain in computer science for almost 30 years now. This rising popularity follows closely the number of data collected all around the world. Each and every internet user produces a huge amount of content during his lifetime. Recommender systems proactively help users to navigate these pieces of information by gathering, and selecting the items to users' needs. In this paper, we discuss the possibility and interest of applying our Multi-Objective Ant Colony System called AntRS to recommend items in different application domains. In particular, we show how our model performs better than the state-of-the-art models with music dataset, and describe our work-in-progress with the museum of fine arts in Nancy (France). The motivation behind this change of application domain is the recommendation of progressive sequences rather than unordered lists of items. en
heal.sponsor This publication is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 693150 en
heal.fullTextAvailability false
heal.conferenceName 11th Workshop on Adaptive and Learning Agents (ALA 2019), in conjunction with the ACM International Conference on Autonomous Agents and Multiagent Systems AAMAS 2019. Montreal, Canada, May, 2019 en
heal.conferenceItemType full paper


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Εμφάνιση απλής εγγραφής

Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες Εκτός από όπου ορίζεται κάτι διαφορετικό, αυτή η άδεια περιγράφεται ως Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες