Abstract
Constraints and preferences coexist in a wide variety of real world applications. In a previous work we have proposed a preference-based online shopping system that handles both constraints as well as preferences where these latter can be in a qualitative or a quantitative form. Given online shoppers’ requirements and preferences, the proposed system provides a set of suggested products meeting the users’ needs and desires. This is an improvement to the current shopping websites where the clients are restricted to choose among a set of alternatives and not necessarily those meeting their needs and satisfaction.
For a better management of constraints and preferences, we extend in this paper the well known constrained CP-Net model to quantitative constraints and integrate it into our system. This extended constrained CP-Net takes a set of constraints and preferences expressing user’s requirements and desires, and returns a set of outcomes provided in the form of list of suggestions. This latter list is sorted according to user’s preferences. An experimental evaluation has been conducted in order to assess the time efficiency of the proposed model to return the list of suggestions to the user. The results show that the response time is acceptable when the number of attributes is of manageable size.
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Acknowledgments
Bandar Ghalib Mohammed and Eisa Alanazi are sponsored by the Ministry of Higher Education, Saudi Arabia.
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Mohammed, B., Mouhoub, M., Alanazi, E. (2015). Combining Constrained CP-Nets and Quantitative Preferences for Online Shopping. In: Ali, M., Kwon, Y., Lee, CH., Kim, J., Kim, Y. (eds) Current Approaches in Applied Artificial Intelligence. IEA/AIE 2015. Lecture Notes in Computer Science(), vol 9101. Springer, Cham. https://doi.org/10.1007/978-3-319-19066-2_68
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DOI: https://doi.org/10.1007/978-3-319-19066-2_68
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