The increase in the number of researchers coupled with the ease of publishing and distribution of scientific papers (due to technological advancements) has resulted in a dramatic increase in astronomy literature. This has likely led to the predicament that the body of the literature is too large for traditional human consumption and that related and crucial knowledge is not discovered by researchers. In addition to the increased production of astronomical literature, recent decades have also brought several advancements in computational linguistics. Especially, the machine-aided processing of literature dissemination might make it possible to convert this stream of papers into a coherent knowledge set. In this paper, we present the application of computational linguistics techniques to astronomy literature. In particular, we developed a tool that will find similar articles purely based on text content f rom an input paper. We find that our technique performs robustly in comparison with other tools recommending articles given a reference paper (known as recommender system). Our novel tool shows great power in combining computational linguistics with astronomy literature and suggests that additional research in this endeavor will likely produce even better tools that will help researchers cope with vast amounts of knowledge being produced.

中文翻译：

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通过基于文本的相似性搜索天文学文献发现知识

研究人员数量的增加以及科学论文的出版和分发（由于技术进步）导致了天文学文献的急剧增加。这很可能导致这样一种困境，即文献体量对于传统人类消费而言太大了，并且研究人员没有发现相关和关键的知识。除了天文文献的产量增加外，近几十年来，计算语言学也取得了一些进展。特别是，文献传播的机器辅助处理可能使将此论文流转换为连贯的知识集成为可能。在本文中，我们介绍了计算语言学技术在天文学文献中的应用。特别是，我们开发了一种工具，可以纯粹基于输入论文中的文本内容来查找类似的文章。我们发现，与其他推荐给定参考论文的文章的工具（称为推荐系统）相比，我们的技术表现稳健。我们的新工具在将计算语言学与天文学文献相结合方面显示出巨大的力量，并表明在这一努力中的额外研究可能会产生更好的工具，帮助研究人员应对产生的大量知识。