远方的发现:预测空间中更远的旅程

T. Cohen, D. Widdows, R. Schvaneveldt, T. Rindflesch
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引用次数: 16

摘要

在本文中,我们扩展了基于谓词的语义索引(PSI)方法,以便在SemRep系统从生物医学文献中提取的谓词数据库中高效地搜索三谓词路径。PSI通过将遍历单个谓词的任务转换为测量复合概念向量之间相似性的任务,避免了可能路径的组合爆炸。因此,一旦构建了相关的概念向量,单个、两个或三个谓词路径的搜索时间是相同的。本文描述了PSI在推断连接治疗相关药物和疾病的示例对的双和三重谓词通路中的应用;并利用这些推断的途径来指导寻找其他疾病的治疗方法。在模拟发现实验中对基于向量的双谓词和三谓词路径搜索的效用进行了评估,发现这些方法是互补的,通过组合应用可以获得最佳性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discovery at a distance: Farther journeys in predication space
In this paper we extend the Predication-based Semantic Indexing (PSI) approach to search efficiently across triple-predicate pathways in a database of predications extracted from the biomédical literature by the SemRep system. PSI circumvents the combinatorial explosion of possible pathways by converting the task of traversing individual predications into the task of measuring the similarity between composite concept vectors. Consequently, search time for single, double or triple predicate paths is identical once the relevant concept vectors have been constructed. This paper describes the application of PSI to infer double and triple predicate pathways connecting example pairs of therapeutically related drugs and diseases; and to use these inferred pathways to guide search for treatments for other diseases. In an evaluation of the utility of vector-based dual- and triple-predicate path search in a simulated discovery experiment, these approaches are found to be complementary, with best performance obtained through their application in combination.
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