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Sharing Online Cultural Experiences: An Argument-Based Approach

  • Conference paper
Modeling Decisions for Artificial Intelligence (MDAI 2012)

Abstract

This paper proposes a system that allows a group of human users to share their cultural experiences online, like buying together a gift from a museum or browsing simultaneously the collection of this museum. We show that such application involves two multiple criteria decision problems for choosing between different alternatives (e.g. possible gifts): one at the level of each user, and one at the level of the group for making joint decisions. The former is made manually by the users via the WeShare interface. This interface displays an image with tags reflecting some features (criteria) of the image. Each user expresses then his opinion by rating the image and each tag. A user may change his choices in light of a report provided by his WeShare agent on the opinion of the group. Joint decisions are made in an automatic way. We provide a negotiation protocol which shows how they are reached. Both types of decisions are based on the notion of argument. Indeed, a tag which is liked by a user constitutes an argument pro the corresponding image whereas a tag which is disliked gives birth to a cons argument. These arguments may have different strengths since a user may express to what extent he likes/dislikes a given tag. Finally, the opinion analysis performed by a WeShare agent consists of aggregating the arguments of the users.

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Amgoud, L. et al. (2012). Sharing Online Cultural Experiences: An Argument-Based Approach. In: Torra, V., Narukawa, Y., López, B., Villaret, M. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2012. Lecture Notes in Computer Science(), vol 7647. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34620-0_26

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  • DOI: https://doi.org/10.1007/978-3-642-34620-0_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34619-4

  • Online ISBN: 978-3-642-34620-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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