BMExpert: Mining MEDLINE for Finding Experts in Biomedical Domains Based on Language Model
BMExpert: Mining MEDLINE for Finding Experts in Biomedical Domains Based on Language Model
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DOI：
10.1109/tcbb.2015.2430338
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发表时间：
2015-11
期刊：
影响因子：
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通讯作者：
Beichen Wang;Xiaodong Chen;Hiroshi Mamitsuka;Shanfeng Zhu
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文献类型：
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作者：
Beichen Wang;Xiaodong Chen;Hiroshi Mamitsuka;Shanfeng Zhu
随着生物医学科学的快速发展，大量文献被发表，以报道新的科学发现，推动知识发现的进程。截至2013年底，全球最大的生物医学文献数据库MEDLINE已经收录了超过2300万篇摘要。因此，科学专业人员在生物医学领域找到某个主题的专家并不容易。在现有的服务，使用一些特设的方法相比，我们开发了一种新的解决方案，生物医学专家发现，BMExpert，语言模型的基础上。为了找到与特定主题查询最相关的生物医学专家，BMExpert通过考虑三个重要因素来挖掘MEDLINE文档：文档与查询主题的相关性，文档的重要性以及文档与专家之间的关联。BMExpert的性能在基准数据集上进行了评估，该基准数据集是通过收集ISMB过去三年（2012-2014）中14个不同主题的计划委员会成员而构建的。实验结果表明，BMExpert在MAP（平均精度）和P@50（精度）方面优于三种现有的生物医学专家发现服务：JANE，GoPubMed和eTBLAST。BMExpert可在http://datamining-iip.fudan.edu.cn/service/BMExpert/上免费访问。
With the rapid development of biomedical sciences, a great number of documents have been published to report new scientific findings and advance the process of knowledge discovery. By the end of 2013, the largest biomedical literature database, MEDLINE, has indexed over 23 million abstracts. It is thus not easy for scientific professionals to find experts on a certain topic in the biomedical domain. In contrast to the existing services that use some ad hoc approaches, we developed a novel solution to biomedical expert finding, BMExpert, based on the language model. For finding biomedical experts, who are the most relevant to a specific topic query, BMExpert mines MEDLINE documents by considering three important factors: relevance of documents to the query topic, importance of documents, and associations between documents and experts. The performance of BMExpert was evaluated on a benchmark dataset, which was built by collecting the program committee members of ISMB in the past three years (2012-2014) on 14 different topics. Experimental results show that BMExpert outperformed three existing biomedical expert finding services: JANE, GoPubMed, and eTBLAST, with respect to both MAP (mean average precision) and P@50 (Precision). BMExpert is freely accessed at http://datamining-iip.fudan.edu.cn/service/BMExpert/.