Bayesian ontology querying for accurate and noise-tolerant semantic searches
Bayesian ontology querying for accurate and noise-tolerant semantic searches
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DOI：
10.1093/bioinformatics/bts471
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发表时间：
2012-10-01
期刊：
影响因子：
5.8
通讯作者：
Robinson, Peter N.
中科院分区：
文献类型：
--
作者：
Bauer, Sebastian;Koehler, Sebastian;Robinson, Peter N.
动机：本体提供了知识领域的概念以及它们之间关系的结构化表示。属性本体用于描述一个领域的项目的特征，例如蛋白质的功能或疾病的体征和症状，这打开了在项目数据库中搜索与观察到的或期望的属性列表最匹配的项目的可能性。然而，由于数据中的噪声、典型查询中的不精确以及单个项目可能无法显示其所属类别的所有属性，朴素搜索方法在实际数据上的表现并不好。结果：我们提出了一种将本体论分析与贝叶斯网络相结合的方法来处理噪声、不精确和属性频率，并展示了我们的方法作为人类遗传学差异诊断支持系统的应用。
Motivation: Ontologies provide a structured representation of the concepts of a domain of knowledge as well as the relations between them. Attribute ontologies are used to describe the characteristics of the items of a domain, such as the functions of proteins or the signs and symptoms of disease, which opens the possibility of searching a database of items for the best match to a list of observed or desired attributes. However, naive search methods do not perform well on realistic data because of noise in the data, imprecision in typical queries and because individual items may not display all attributes of the category they belong to.Results:: We present a method for combining ontological analysis with Bayesian networks to deal with noise, imprecision and attribute frequencies and demonstrate an application of our method as a differential diagnostic support system for human genetics.