| Summary: | 碩士 === 淡江大學 === 資訊管理學系碩士班 === 104 === In this work, we will present a recommender system which combines the collaborative and content-based methods using the Bayesian network. Given a book, it can provide related book recommendation without knowing the user identity so that users can look up the desired books more easily and the library books can be utilized more efficiently. Currently, few libraries provide a book recommender system. For those libraries which provide the recommender system, the user must login to receive the recommended book list. But users are accustomed to looking up the books without login to save the trouble or the risk of being tracked. This work aims to provide an anonymous way of book recommendation about a book without knowledge of the user identity.
In our offline experiments, the results show that under the framework of the Bayesian network, adding the keyword nodes and the subject code nodes can help promote the recommendation performance when compared with the traditional recommendation methods. This work also conducts an online user experiment to demonstrate the usefulness of our recommendation method.
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