Citations are ubiquitous in scientific articles and play important roles for representing the semantic content of a full-text biomedical article. In this work, we manually examined full-text biomedical articles to analyze the semantic content of citations in full-text biomedical articles. After developing a citation relation schema and annotation guideline, our pilot annotation results show an overall agreement of 0.71, and here we report on the research challenges and the lessons we've learned while trying to overcome them. Our work is a first step toward automatic citation classification in full-text biomedical articles, which may contribute to many text mining tasks, including information retrieval, extraction, summarization, and question answering.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3003334 | PMC |
| http://dx.doi.org/10.1109/BIBMW.2009.5332080 | DOI Listing |
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