[Objective] This paper tries to improve the traditional content recommendation service of digital literature, which cannot fully exploit the semantic information of the literature. [Methods] First, we introduced the Ontology reasoning rules to the recommendation system, and then semantically extended the user’s query. Second, we calculated the similarity of the literature to rank. Finally, we recommend those top ranked literature to the users. [Results] The proposed algorithm can calculate the semantic similarity among literature and successful recommend documents to the users. [Limitations] Only examined the new method with relatively small data sets. [Conclusions] The proposed algorithm could effectively exploit the semantic information of target literature and offer a new way to recommend digital resource to the users.
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