2011
DOI: 10.1016/j.is.2011.06.004
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Managing contextual preferences

Abstract: a b s t r a c tTo handle the overwhelming amount of information currently available, personalization systems allow users to specify through preferences which pieces of data interest them. Most often, users have different preferences depending on context. In this paper, we introduce a model for expressing such contextual preferences. Context is modeled using a set of hierarchical attributes, thus allowing context specification at various levels of detail. We formulate the context resolution problem as the probl… Show more

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Cited by 43 publications
(33 citation statements)
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“…Time is modeled here as a multidimensional attribute. The dimensions of time have a hierarchical structure, that is, time values are organized at different levels of granularity (similar to [16,18]). In particular, we consider three different levels over time: time of day, day of week and time of week with domain values {"morning", "afternoon", "evening", "night"}, {"Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"} and {"Weekday", "Weekend"}, respectively.…”
Section: Temporal Context-based Recommendationsmentioning
confidence: 99%
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“…Time is modeled here as a multidimensional attribute. The dimensions of time have a hierarchical structure, that is, time values are organized at different levels of granularity (similar to [16,18]). In particular, we consider three different levels over time: time of day, day of week and time of week with domain values {"morning", "afternoon", "evening", "night"}, {"Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"} and {"Weekday", "Weekend"}, respectively.…”
Section: Temporal Context-based Recommendationsmentioning
confidence: 99%
“…The selection of the appropriate preferences can be made more efficient by deploying indexes on the context of the preferences. Such a data structure that exploits the hierarchical nature of context, termed profile tree, is introduced in [18].…”
Section: Computing Recommendationsmentioning
confidence: 99%
“…Our initial work 18 was somewhat inspired by the approach proposed by Stefanidis et al 9,10,19 . Hereafter, we review this approach in a more detailed way and highlight some of its basic shortcomings.…”
Section: Stefanidis Et Al's Approachmentioning
confidence: 99%
“…Contextual preferences (i.e., preferences that depend on context) have recently attracted considerable attention in many research fields 2,3,4,5,6,7,8,9 . In the database field, one of the most interesting works about contextual preferences is that by Stefanidis et al 9,10,11 .…”
Section: Introductionmentioning
confidence: 99%
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