Weighted granular best matching algorithm is proposed for the operation of context matching in context-aware computing systems. New algorithm deals with the subjective, fuzzy and multidimensional characteristics of contextual information by using weights and a granular structure for contextual information. The proposal is applied on a case: CAPRA &ndash / Context-Aware Personal Reminder Agent tool to show the applicability of the new context matching algorithm. The obtained outputs showed that proposed algorithm produces the results which are more sensitive to the user&rsquo / s intention, more adaptive to the characteristics of the contextual information and applicable to a current Context-aware system.