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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Identification of Biomedical Articles with Highly Related Core Contents
verfasst von : Rey-Long Liu
Erschienen in: Intelligent Information and Database Systems
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Abstract
Given a biomedical article a, identification of those articles with similar core contents (including research goals, backgrounds, and conclusions) as a is essential for the survey and cross-validation of the highly related biomedical evidence presented in a. We thus present a technique CCSE (Core Content Similarity Estimation) that retrieves these highly related articles by estimating and integrating three kinds of inter-article similarity: goal similarity, background similarity, and conclusion similarity. CCSE works on titles and abstracts of biomedical articles, which are publicly available. Experimental results show that CCSE performs better than PubMed (a popular biomedical search engine) and typical techniques in identifying those scholarly articles that are judged (by biomedical experts) to be the ones whose core contents focus on the same gene-disease associations. The contribution is essential for the retrieval, clustering, mining, and validation of the biomedical evidence in literature.