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Investigating Distributed Approaches to Efficiently Extract Textual Evidences for Biomedical Ontologies

Abstract : Heterogeneous data resources in biomedicine be- come available both in structured and unstructured formats, such as scientific publications and healthcare guidelines com- pared to formal biomedical ontologies and controlled vocabu- laries. Increasing researches focus on bridging the gaps among the heterogeneous data to discovery implicit knowledge. To make this happen, efficient computational approaches are a necessity for applications in such a knowledge- and data- intensive domain. In this paper, we first define a particular task, relation alignment, which is to identify textual evidences for biomedical ontologies. Then, we investigate two parallel ap- proaches for this task over distributed systems and present the details of their implementations. Moreover, we characterize the performance of our methods through extensive experiments, thereby allowing researchers to make a more informed choice in the presence of large-scale biomedical data.
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https://hal.archives-ouvertes.fr/hal-01139036
Contributor : Yue Ma <>
Submitted on : Friday, April 3, 2015 - 11:43:35 AM
Last modification on : Thursday, January 7, 2021 - 2:30:03 PM

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  • HAL Id : hal-01139036, version 1

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Yue Ma, Cheng Long. Investigating Distributed Approaches to Efficiently Extract Textual Evidences for Biomedical Ontologies. 14th IEEE International Conference on Bioinformatics and BioEngineering (BIBE'14), 2014, Boca Raton, United States. ⟨hal-01139036⟩

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