Contextual hybrid-based recommendation of Pubmed articles
Background: The amount of information in the medical field has been growing day by day. Also new medical articles about the preoccupied disease are published each day and the updated information is very required by physicians. The appropriate information in the appropriate moment is the goal of this research work.
Methods: Our goal is to recommend documents deemed relevant to doctors regarding the context of using a management application for electronic medical records. The principle is to extract the context of this usage: illness, Age ..., searching in the contents of documents and taking into account the rate of vote documents. For experiment and evaluation, we have used 100 articles randomly selected from pubmed about cardiology. In addition, we have developed a system that extracts the context of medical record system at the moment of exploration. The extracted context is used with users rating by the recommender system to select and rank the recommended articles for physicians in the same moment of use.
Results: The first result of this research work is the smart interaction between users and the software system by introducing the context of use. In addition, another important result is the reuse of userâ€™s appreciation for more dynamicity and intelligibility.
Conclusion: The developed system offers the physician an appropriate recommendation of selected pubmed articles. The developed system augments the relevancy of the recommendation by analyzing the contents of articles and introducing a collaborative method.
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