ID 原文 译文
56768 此外,总结了相关的一系列推荐应用场景.最后,提出了对基于知识图谱的推荐系统前景的看法,并展望了该领域未来的研究方向. Finally,we present our opinions on the prospects of KG-based RS and suggest some future research directions in this area.
56769 以研究科学创新与演化规律为目的的科学学近年来迎来了进一步的发展,科技大数据领域知识图谱在其中发挥了重大的作用. Recently, the knowledge graph (KG) of sci-tech and big data technology has played a paramount rolein the development of the science of science.
56770 本文将从科技大数据知识图谱构建及应用研究角度,对科学学研究过程中发挥重大推动作用的科技领域知识图谱技术进行系统、深入的综述,阐述科技大数据知识图谱构建过程中涉及的科技实体抽取、科技实体消歧、科技关系抽取、科技关系推断等问题,对科技实体推荐、科技社区发现、科技实体评价、学科交叉以及学科演化等科技大数据知识图谱分析挖掘方法进行系统梳理,并给出科技大数据知识图谱未来的研究及应用方向. We carry out a systematic and in-depth review of KG construction andbig data technology application in the sci-tech field. Specifically, we explain the issues of sci-tech entity extraction,sci-tech entity disambiguation, sci-tech relationship extraction, and sci-tech relationship inference involved in theconstruction of sci-tech big data KG, and give a systematized summary of the analysis and mining methods ofthe sci-tech big data KG, such as sci-tech entity recommendation, sci-tech community detection, sci-tech entityevaluation, interdisciplinary research, and disciplinary evolution analysis. Lastly, we give the future research andapplication directions of the sci-tech KG.
56771 随着大数据对全球生产、流通、分配、消费等国计民生领域产生重要影响,事理作为认知智能重要概念,不仅帮助人们发现大数据所蕴含的国计民生的线索与发展规律,而且帮助人们更好认知人机物三元世界未来发展趋势. Along with the increasing impact of big data on the economic operation mechanism, including globalproduction, circulation, distribution and consumption, event logic (EL) is becoming an important concept inmining and releasing the potential value of big data. Besides its critical role in exploring the clues and rules ofdigital economy, EL will also help people better understand the future development of the ternary human-cyber?physical universe.
56772 考虑到人机物事理动态演化是工业大数据有别于其他行业大数据处理的本质区别,本文从人机物事理动态演化特性智能认知着手,结合传统知识图谱在互联网领域取得的成功经验,提出了面向大数据领域的事理认知图谱构建与推断分析. Considering the dynamic evolution of the EL is the essential difference between industrial bigdata and other big data. Therefore, we propose a constructing and inferring EL cognitive graph in the field of bigdata. Firstly, we introduce the great opportunities offered by the knowledge graph in promoting the high-qualitydevelopment of the manufacturing industry, leading the economic development of the new digital manufacturingindustry, and promoting the cross-development of sociology and information science.
56773 首先论述了事理认知图谱对推动认知智能研究发展的贡献,剖析了它与知识图谱异同之处,深度理解人类社会发展变化规律的重要价值.其次阐述了事理抽取与泛化、多模态联合网络化合成表示、进化认知和推断分析等关键技术研究最新进展以及面临的挑战.最后,结合我们课题组在事理认知图谱的研究进展情况,归纳总结了事理认知图谱在预防网络电话诈骗和安全生产管控等领域最新应用效果. Secondly, we present theconstruction technology of EL cognitive graph and expound the progress and critical technical challenges inthe research of the EL cognitive graph at home and abroad, in the aspects of multi-granularity acquisition andrepresentation of EL, multimodal association and fusion, evolution analysis and mining of EL behavior.
56774 本文结尾总结和展望事理认知图谱的未来研究方向和发展前景. Finally,combined with the research progress of our works in EL cognitive graph, we summarize the effect of EL cognitivegraph in the prevention of network fraud and the control of safe production as well as summarize and anticipatethe future research direction and development prospect of the industry.
56775 一个准确丰富的人物关系图谱不仅能够为大众提供人物实体的清晰介绍和人物之间的相互关联,而且能够为智能服务系统提供有效的知识支持. An accurate and rich inter-personal relation knowledge graph (KG) not only provides a clear intro?duction of persons and the interconnections among them but also provide knowledge support for the intelligentservice system.
56776 目前大多知识来源均以百科类表格数据为起点,在此基础上构建知识图谱. At present, most KGs are based on the encyclopedia tabular data.
56777 本文主要描述如何充分利用百科类文本数据构建高质量的人物关系图谱. In this article, we mainlydescribe how to make full use of encyclopedic text to build a high-quality inter-personal relation KG.