基于语义Web技术的研究门户数据响应式框架
A Responsive Framework for Research Portals Data using Semantic Web Technology
AI总结：
针对研究人员从多源收集数据耗时费力的问题，提出一个基于语义Web技术的研究门户数据响应式框架，从Microsoft Academic和IEEE Xplore提取信息，实现语义组织，提升数据可访问性与知识发现效率。
摘要：
随着万维网上数据量持续呈指数级增长，对语义结构化信息的访问仍然有限。语义Web应运而生，作为一种解决方案，旨在增强数据的机器可读性，使其更易于访问和解释。不同网站已采用多种技术（如网络抓取和映射）来提供语义访问。网络抓取涉及利用强大的字符串操作，从多种数据源（如万维网）中提取有价值的信息。在研究领域，研究人员面临从多个来源收集相关数据的挑战，这需要耗费大量时间和精力。本研究旨在通过设计一个用于研究门户数据语义组织的框架来解决这一问题。该框架专注于从两个特定研究门户（即Microsoft Academic和IEEE Xplore）提取信息。其主要目标是从这些目标来源收集多样化的研究相关数据。通过实施该框架，研究人员可以简化为其工作收集有价值信息的过程，节省时间和精力。研究门户数据的语义组织提供了增强的可访问性和可解释性，促进了更有效和高效的知识发现。本研究有助于推进研究数据管理，并促进语义Web技术在学术界中的应用。
英文摘要：
As the amount of data on the World Wide Web continues to grow exponentially, access to semantically structured information remains limited. The Semantic Web has emerged as a solution to enhance the machine-readability of data, making it significantly more accessible and interpretable. Various techniques, such as web scraping and mapping, have been employed by different websites to provide semantic access. Web scraping involves the extraction of valuable information from diverse data sources, such as the World Wide Web, utilizing powerful string manipulation operations.In the research field, researchers face the challenge of collecting relevant data from multiple sources, which requires substantial time and effort. This research aims to address this issue by designing a framework for the semantic organization of research portal data. The framework focuses on the extraction of information from two specific research portals, namely Microsoft Academic and IEEE Xplore. Its primary objective is to gather diverse research-related data from these targeted sources.By implementing this framework, researchers can streamline the process of collecting valuable information for their work, saving time and effort. The semantic organization of research portal data offers enhanced accessibility and interpretability, facilitating more effective and efficient knowledge discovery. This research contributes to the advancement of research data management and promotes the utilization of semantic web technologies in the academic community.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
