摘要：【中文】本发明实施例提供了一种基于局部加权中心性信任推理的信息推荐方法及装置，方法包括：计算每个用户对其邻居用户的信任信息所对应的预设分数的总和，作为每个用户的局部加权中心性分数；针对每个用户，根据对应的局部加权中心性分数对其邻居用户进行筛选，得到该用户的目标邻居用户；根据待推荐用户与其目标邻居用户之间的兴趣关联关系，以及目标用户与其他用户之间的兴趣关联关系，确定待推荐用户与目标用户之间的目标兴趣关联关系；基于目标兴趣关联关系对应的各用户之间的信任信息所对应的预设分数，确定待推荐用户对目标用户的信任分数；根据信任分数，向待推荐用户推荐预设信息。应用本发明实施例，可以提高信息推荐的效率。 【EN】The embodiment of the invention provides an information recommendation method and device based on local weighted centrality trust reasoning, wherein the method comprises the following steps: calculating the sum of preset scores corresponding to the trust information of each user to the neighbor users of each user, and taking the sum as the local weighted centrality score of each user; aiming at each user, screening neighbor users according to the corresponding local weighted centrality score to obtain target neighbor users of the user; determining a target interest association relation between a user to be recommended and a target user according to the interest association relation between the user to be recommended and a target neighbor user of the user to be recommended and the interest association relation between the target user and other users; determining the trust score of the user to be recommended to the target user based on the preset score corresponding to the trust information between the users corresponding to the target interest association relation; and recommending preset information to the user to be recommended according to the trust score. By applying the embodiment of the invention, the information recommendation efficiency can be improved.