An Ontology-based Framework for Analysis Recommendation

被引：0

作者：

Henriques, Gabriela ^{[1
]}

Stacey, Deborah ^{[1
]}

机构：

[1] Univ Guelph, Sch Comp Sci, Guelph, ON, Canada

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE) | 2014年

关键词：

Ontology; Knowledge Engineering; Data Analysis; Analysis Recommendation; Leveraging Knowledge; Syndromic Surveillance;

D O I：

10.1109/BIBE.2014.70

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

One of the challenges with data analysis revolves around selecting the best analysis method for a data set that will provide appropriate and meaningful results. This paper presents an ontology-based framework to address challenges around selecting an analysis method that can best represent a data set and the information you want to get out of it. Two ontologies were developed, one to capture semantic and syntactic descriptions on a data source, and likewise one to capture the description of analysis methods. Ontologies were selected for their flexibility in providing a description between a set of concepts and relationships along with their ability to reason between these descriptions.

引用

页码：277 / 282

页数：6

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