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借鉴协同过滤个性化推荐思想,提出基于同行评价计算用户相似度的学术论文个性化推荐-传播平台模型:研究人员借助推荐-传播系统将自己或他人的学术论文推荐给与其有相似研究兴趣的网络邻居,从而可基于同行协同过滤将学术文献高效获取和研究成果主动推介结合起来。运用计算机多主体仿真方法,本文模拟并验证了推荐-传播平台的性能。
Based on the idea of collaborative filtering personalized recommendation, this paper proposes a personalized recommendation of academic essay based on peer evaluation to calculate user similarity. - Propagation platform model: Researchers recommend themselves or others’ academic essays to networks with similar research interests through recommendation-dissemination system Neighbors, which can be based on peer collaborative filtering of academic literature and efficient access to research results to promote the combination of. Using computer multi-agent simulation method, this paper simulates and verifies the performance of recommendation-propagation platform.