Design and implementation of an evolutional data collecting system for the atomic and molecular databases

原子和分子数据库在基础科学和工业应用的广泛领域中是有用的。根据目前的数据库开发程序，原子和分子数据主要是通过数据中心科学家的辛勤工作从科学论文中收集的。在这项研究中，我们已经调查了一个新的应用信息技术的进化发展的原子和分子数据库的基础上，通过互联网的科学论文的自动收集。我们开发了一个机器学习软件，可以识别未知文章中原子和分子数据的存在，使用电子激发和电离截面的书目数据库作为训练示例。为了表征文章，我们首先使用训练和测试示例中的术语频率。其次，我们使用的原子和分子的状态和原子和分子物理学，这是有用的，以提高识别的准确性相应的技术术语的信息。我们研究的方法，以识别的原子和离子的物种，电荷状态，电子组态，光谱项在电子形式的科技论文的表达式。我们调查的频率出现的每一个表达式在不同领域的论文发表在物理学评论A至E期刊。核种和分子的表达也被分别识别，这被发现是有用的，以区分那些为核物理以及凝聚态物理的原子物理论文。结合互联网搜索引擎，本研究结果将使人们有可能收集不仅是从文章的原子和分子数据，但更广泛的科学信息，在广泛的研究领域。

Atomic and molecular database is useful for wide variety of fields of basic science and industrial applications. According to the present procedure of database development, atomic and molecular data are mainly collected from scientific papers through laborious work of staff scientists in the data centers. In this study, we have investigated a new application of information technology for evolutional development of atomic and molecular database based on automatic collection of scientific papers through the internet. We have developed a machine learning software which can recognize the existence of atomic and molecular data in unknown articles, using the bibliographic database of electron excitation and ionization cross sections as training examples. In order to characterize the articles, we firstly use the frequency of terms in the training and test examples. Secondly, we use information on the atomic and molecular states and technical terms corresponding to the atomic and molecular physics, which is found to be useful for improving the accuracy of the recognition. We study methods to recognize expressions for atomic and ionic species, charge states, electron configuration, spectral terms in the electronic form of scientific papers. We investigate frequency of appearance of each expression in the papers from different fields of physic published in Phys. Rev. A to E journals. Expression for nuclear species and molecules are also recognized separately, which are found to be useful to distinguish papers for atomic physics from those for the nuclear physics as well as physics of the condensed matter. Combining with the internet search engines, present result will make one possible to collect not only atomic and molecular data from articles but broader scientific information over a wide range of research fields.