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Retrieval of Highly Related Biomedical References by Key Passages of Citations

机译:通过引用的关键段落检索高度相关的生物医学参考文献

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Biomedical researchers often need to carefully identify and read multiple articles to exclude unproven or controversial biomedical evidence about specific issues. These articles thus need to be highly related to each other. They should share similar core contents, including research goals, methods, and findings. However, given an article r, existing search engines and information retrieval techniques are difficult to retrieve highly related articles for r. We thus present a technique KPC (key passage of citations) that extracts key passages of the citations (out-link references) in each article, and based on the key passages, estimates the similarity between articles. Empirical evaluation on over ten thousand biomedical articles shows that KPC can significantly improve the retrieval of those articles that biomedical experts believe to be highly related to specific articles. The contribution is of practical significance to the writing, reviewing, reading, and analysis of biomedical articles.
机译:生物医学研究人员通常需要仔细识别并阅读多篇文章,以排除关于特定问题的未经证实或有争议的生物医学证据。因此,这些文章需要彼此高度相关。他们应该共享相似的核心内容,包括研究目标,方法和发现。但是,给定文章r,现有的搜索引擎和信息检索技术很难检索与r高度相关的文章。因此,我们提出了一种技术KPC(引文的关键段落),该技术提取每篇文章中引文的关键段落(链接参考),并基于这些关键段落估计文章之间的相似度。对上万份生物医学文章的经验评估表明,KPC可以显着改善生物医学专家认为与特定文章高度相关的那些文章的检索。该贡献对于生物医学文章的撰写,审阅,阅读和分析具有实际意义。

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