Abstract
This article describes a new personalization process on decisional queries through a new approach of triadic association rules mining. This process uses the query log files of users and models them in new way by taking into account their triadic aspect. To validate our approach, we developed a personalization software prototype P-TRIAR (Personalization based on TRIadic Association Rules) which extracts two types of rules from query log files. The first one will serve to query recommendation by taking into account the collaborative aspect of users during their decisional analysis. The second type of rules will enrich user queries. The approach is tested on a real data warehouse to show the compactness of triadic association rules and the refined personalization which we propose.
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Ali, S.S., Boussaid, O., Bentayeb, F. (2014). P-TRIAR: Personalization Based on TRIadic Association Rules. In: Manolopoulos, Y., Trajcevski, G., Kon-Popovska, M. (eds) Advances in Databases and Information Systems. ADBIS 2014. Lecture Notes in Computer Science, vol 8716. Springer, Cham. https://doi.org/10.1007/978-3-319-10933-6_18
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DOI: https://doi.org/10.1007/978-3-319-10933-6_18
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