Semantic Technologies for Scientific Literature Management (v2)

科学文献管理语义技术 (v2)

• 批准号: RGPIN-2016-06683
• 负责人: Witte, René
• 金额: $ 1.6万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=678876
• 关键词: Semantic; Technologies; Scientific; Literature; Management

A typical day in the life of a researcher involves finding, reading and analyzing scientific literature that are related to her task at hand. Online digital libraries, academic publishing databases and open access repositories grant access to a plethora of information, which poses major challenges to researchers when trying to obtain the information they need: Most modern search engines return thousands of articles in a matter of seconds and researchers have to manually comb through the results to find the information that may aid them in their research activities a time-consuming and laborious task, during which critical knowledge can be easily missed. This apparent disproportion of humans' capabilities in processing information versus the unprecedented rate of scientific publishing growth has encouraged researchers from various domains to look for new approaches to extract, organize, and manage knowledge from the immense amount of available literature in ever-growing repositories. The frontiers of these explorations are researchers from the thriving domain of semantic publishing a synergic community of semantic web researchers, computational linguists, librarians and publishing companies aiming towards a platform for dissemination of scientific literature accessible to both humans and machines.******With this proposal, we are joining the movement, by developing new methodologies for transforming scientific literature from written content in isolation into a queryable web of documents suitable for machine interpretation. We conceptualize the myriad of possibilities that such a knowledge base can provide for researchers in form of a Personal Research Agent that helps researchers in finding, writing and learning from scientific literature. We demonstrate how a confluence of state-of-the-art techniques from the Semantic Web and Natural Language Processing domains can realize a proactive agent that can offer personalized services to researchers in retrieval and understanding of scientific literature, based on their background knowledge, interests and tasks. The agent's knowledge base, is populated with knowledge automatically extracted from scientific literature of a given domain using text mining techniques. We represent the structure and semantics of scientific literature to the agent by formalizing its rhetorical blocks and topics discussed within its content using semantic web technologies and the wealth of knowledge available in the Linked Open Data (LOD) cloud. Similarly, we introduce researchers to the agent through their \emph{profiles} that contain a formal representation of their personal metadata, interests, tasks and background knowledge.******Our approach is the first to exploit the opportunities of linking a formal model of users and scientific publications in order to offer novel, personalized services to reduce a researcher's information overload.

研究人员的日常工作包括查找、阅读和分析与其手头任务相关的科学文献。在线数字图书馆、学术出版数据库和开放存取存储库提供了大量信息，这给研究人员在试图获得所需信息时带来了重大挑战：大多数现代搜索引擎在几秒钟内返回数千篇文章，研究人员不得不手动梳理结果，以找到可能有助于他们研究活动的信息-消耗和费力的任务，在此期间，关键知识很容易被遗漏。人类处理信息的能力与科学出版物前所未有的增长速度之间的这种明显不成比例，鼓励来自各个领域的研究人员寻找新的方法来从不断增长的知识库中的大量可用文献中提取，组织和管理知识。这些探索的前沿是来自蓬勃发展的语义出版领域的研究人员，这是一个由语义网研究人员、计算语言学家、图书馆员和出版公司组成的协同社区，旨在建立一个人类和机器均可访问的科学文献传播平台。**有了这个提议，我们正在加入这一运动，通过开发新的方法，将科学文献从孤立的书面内容转化为适合机器解释的可查询文档网络。我们概念化的无数的可能性，这样的知识库可以为研究人员提供一个个人研究代理，帮助研究人员在寻找，写作和学习科学文献的形式。我们展示了如何融合的国家的最先进的技术从语义Web和自然语言处理领域可以实现一个主动代理，可以提供个性化的服务，研究人员在检索和理解科学文献，根据他们的背景知识，兴趣和任务。代理的知识库，填充知识自动提取的科学文献中的一个给定的领域，使用文本挖掘技术。我们代表的结构和语义的科学文献的代理，通过形式化的修辞块和主题讨论的内容，使用语义Web技术和丰富的知识，在关联开放数据（LOD）云。同样，我们通过研究人员的个人资料向代理介绍他们的个人资料，这些资料包含他们个人元数据，兴趣，任务和背景知识的正式表示。我们的方法是第一个利用连接用户和科学出版物的正式模型的机会，以提供新颖的，个性化的服务，以减少研究人员的信息过载。