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The current assistive device matching for the disabled usually rely on human source,which has been challenged as too inefficiency and inaccuracy to satisfy the needs of the disabled.With the increasing number of assistive devices and the disabled,more and more provenance data are generated,data utilization,however,is very low.Provenance plays a key role in different disciplines to track several characteristics of the origin of data.It is important and valuable to explore how to take full advantage of provenance to discover knowledge and help match the assistive devices for the disabled.This paper proposes a provenance-based solution for the assistive devices matching process.We first propose an instantiated instance provenance based on open provenance model for personalized recommendation.Then we formulate the matching process and propose a personalized recommendation algorithm,which combines the multi-instance model and provenance information.Furthermore,we present a new personalized recommendation prototype architecture,that integrates the provenance model and recommendation algorithm and discuss the applicability of the architecture using in practical environment.