Most researchers establish research directions in their study of new fields by providing expert advice or publishing expert papers. The existing academic search services display papers by field but do not provide experts by field. Therefore, researchers are left to judge experts in each field by analyzing the papers for themselves. In this paper, we design and implement an expert search system based on papers that have been published in the academic societies. The academic expert search system is based on a big data processing system to handle a large amount of data in academic fields. It calculates an expert score using quality and influence factors. The quality factor is calculated based on the citations, impact factor, and recentness of a paper. The influence factor is measured by the sparsity of a field and the degree of contributiveness of an author. The proposed system provides various services such as expert searches, keyword searches, the hot topics, expert relationships, and academic society statistics. By finding experts in a specific field, our system can support researchers’ research activities.

大多数研究人员通过提供专家建议或发表专家论文来确定其在新领域研究中的研究方向。现有的学术搜索服务按领域显示论文，但不按领域提供专家。因此，研究人员只能通过自己分析论文来判断各个领域的专家。在本文中，我们基于学术团体已发表的论文设计并实现了一个专家搜索系统。学术专家搜索系统基于大数据处理系统，可处理学术领域中的大量数据。它使用质量和影响因素来计算专家评分。品质因子是根据论文的引文，影响因子和最新程度计算的。影响因子通过字段的稀疏性和作者的贡献程度来衡量。所提出的系统提供各种服务，例如专家搜索，关键字搜索，热门话题，专家关系和学术协会统计数据。通过寻找特定领域的专家，我们的系统可以支持研究人员的研究活动。