Automatic literature metadata extraction from datacite services

作     者：Ma, Kun 

作者机构：Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan250022 China 

出 版 物：《Recent Patents on Computer Science》 (Recent Pat. Comput. Sci.)

年 卷 期：2018年第11卷第1期

页      面：25-31页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0817[工学-化学工程与技术] 08[工学] 0703[理学-化学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work was supported by the National Natural Science Foundation of China (61772231 & 61702217 & 61702216)  the Shandong Provincial Natural Science Foundation (ZR2017MF025 & ZR2014FQ029)  the Shandong Provincial Key R&D Program of China (2015GGX106007 & 2016ZDJS01A12 & 2017CXGC0701 & 2018CXGC0706)  the Science and Technology Program of University of Jinan (XKY1734 & XKY1828) 

主　　题：Extraction 

摘      要：Background: Generally, it is difficult to obtain the literature metadata in a unified way because the source data of literature is heterogeneous. Researchers developed a series of systems marked by digital object to manage them and obtained a good effect. Though there are several DOI systems, we face with some problems in promoting the use of them. Objective: To address this issue of promoting literature identifier extraction, this paper has proposed automatic literature metadata extraction from DataCite services. Method: This paper describes Patent Publication Number CN103279361A, titled Method and System for Bookmark-triggered Literature Sharing, issued by State Intellectual Property Office of the P.R.C. on January 27, 2016. A literature metadata extraction system supporting both personal computer and mobile terminal is developed using the integration of DataCite content negotiation, DataCite metadata search, and HTML template extraction. The architecture of this system is divided into model, view, service and controller. An important contribution of this article is to design a cross-platform and universal way to extract digital literature with/without DOI. Results: The analysis of application s effect and piratical test case show the ability to verify the authenticity of automatic literature metadata extraction from DataCite services. The contributions of our method are literature identifier extraction from DOI proxy, template extraction using Roadrunner, and bookmarklet-based literature sharing. Conclusion: The idea and a disclosed embodiment of a patent (Patent CN103279361A, issued by State Intellectual Property Office of the P.R.C.) are presented, which is based on the distribution of literature metadata extraction. In one disclosed embodiment, this method contains literature identifier extraction from DOI proxy, template extraction using Roadrunner, and bookmarklet-based literature sharing. © 2018 Bentham Science Publishers.