Ranking Biomedical Annotations with Annotator’s Semantic Relevancy
Author
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-05-11
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Biomedical annotation is a common and affective artifact for researchers to discuss, show opinion, and share discoveries.
It becomes increasing popular in many online research communities, and implies much useful information.
Ranking biomedical annotations is a critical problem for data user to efficiently get information.
As the annotator’s knowledge about the annotated entity normally determines quality of the annotations, we evaluate the knowledge, that is, semantic relationship between them, in two ways.
The first is extracting relational information from credible websites by mining association rules between an annotator and a biomedical entity.
The second way is frequent pattern mining from historical annotations, which reveals common features of biomedical entities that an annotator can annotate with high quality.
We propose a weighted and concept-extended RDF model to represent an annotator, a biomedical entity, and their background attributes and merge information from the two ways as the context of an annotator.
Based on that, we present a method to rank the annotations by evaluating their correctness according to user’s vote and the semantic relevancy between the annotator and the annotated entity.
The experimental results show that the approach is applicable and efficient even when data set is large.
American Psychological Association (APA)
Wu, Aihua. 2014. Ranking Biomedical Annotations with Annotator’s Semantic Relevancy. Computational and Mathematical Methods in Medicine،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-458130
Modern Language Association (MLA)
Wu, Aihua. Ranking Biomedical Annotations with Annotator’s Semantic Relevancy. Computational and Mathematical Methods in Medicine No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-458130
American Medical Association (AMA)
Wu, Aihua. Ranking Biomedical Annotations with Annotator’s Semantic Relevancy. Computational and Mathematical Methods in Medicine. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-458130
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-458130