A method of searching for related literature on protein structure analysis by considering a user's intention.
A method of searching for related literature on protein structure analysis by considering a user's intention.
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DOI：
10.1186/1471-2105-16-s7-s4
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发表时间：
2015
影响因子：
3
通讯作者：
Ohkawa T
中科院分区：
文献类型：
--
作者：
Ito A;Ohkawa T
近年来，随着蛋白质结构分析技术的进步，有关蛋白质结构和功能的知识在大量的文章中发表。需要一种从如此庞大的文章库中搜索特定出版物的方法。在本文中，我们提出了一种以文章本身作为查询来搜索蛋白质结构分析相关文章的方法。在提出的方法中，每篇文章都表示为一组概念。然后，通过使用从数据库（如Gene Ontology）中制定的概念之间的相似性，评估文章之间的相似性。在这个框架中，期望的搜索结果取决于用户的搜索意图，因为在一篇文章中包含了各种各样的信息。因此，本文提出的方法不仅提供一个输入文章（主文章），还提供与其相关的附加文章作为输入查询，根据两个查询文章之间的关系来确定用户的搜索意图。换句话说，基于输入文章和附加文章中包含的概念，我们通过改变对每个概念的关注程度和修改概念层次图来实现考虑用户意图的相关文献搜索。我们利用三个查询数据集，从蛋白质数据库中注册的有关蛋白质结构分析的文章中检索相关论文。实验结果表明，与不考虑用户意图时相比，搜索结果的准确率更高，验证了所提方法的有效性。
In recent years, with advances in techniques for protein structure analysis, the knowledge about protein structure and function has been published in a vast number of articles. A method to search for specific publications from such a large pool of articles is needed. In this paper, we propose a method to search for related articles on protein structure analysis by using an article itself as a query. Each article is represented as a set of concepts in the proposed method. Then, by using similarities among concepts formulated from databases such as Gene Ontology, similarities between articles are evaluated. In this framework, the desired search results vary depending on the user's search intention because a variety of information is included in a single article. Therefore, the proposed method provides not only one input article (primary article) but also additional articles related to it as an input query to determine the search intention of the user, based on the relationship between two query articles. In other words, based on the concepts contained in the input article and additional articles, we actualize a relevant literature search that considers user intention by varying the degree of attention given to each concept and modifying the concept hierarchy graph. We performed an experiment to retrieve relevant papers from articles on protein structure analysis registered in the Protein Data Bank by using three query datasets. The experimental results yielded search results with better accuracy than when user intention was not considered, confirming the effectiveness of the proposed method.