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征稿 | Call for papers on Knowledge Graphs
阅读量:4204 次
发布时间:2019-05-26

本文共 4008 字,大约阅读时间需要 13 分钟。

Knowledge graph是Data Intelligence的核心主题和期刊特色之一。为持续展示这一领域的最新进展和前沿成果,Data Intelligence正在与国际学者一道策划两期Knowledge graph专辑。

期待大家关注并积极投稿参与!

DI专辑

Special Issue on Personal Health Knowledge Graphs 

This special issue at Data Intelligence Journal seeks original articles describing theoretical and practical methods and techniques for building and maintaining personal health knowledge graphs.

 

Topics relevant to this special issue include, but are not limited to, the following:

 

  • Definitions of personal health knowledge graphs;

  • Opportunities for the application of personal health knowledge graphs;

  • Challenges of creating and maintaining a personalized health knowledge graph;

  • Opportunities for knowledge graph research in this space such as data integration, data profiling, data curation, data querying, knowledge discovery, ontology mapping, matching, reconciliation, and machine learning approaches.

 

Deadline

Submission deadline: September 30, 2021. Papers submitted before the deadline will be reviewed upon receipt.

 

Guest editors

The guest editors can be reached at senevo@rpi.edu.

Guest editorial board

Ching-HuaChen, IBM

Amar Das, Merck

Ying Ding, University of Texas Austin

Deborah McGuinness, Rensselaer Polytechnic Institute

Marco Monti, IBM

Oshani Seneviratne, Rensselaer Polytechnic Institute

Mohammed J Zaki, Rensselaer Polytechnic Institute

 

Author Guidelines

Submissions shall be made through the ScholarOne system at https://mc03.manuscriptcentral.com/di. Prospective authors must take notice of the submission guidelines posted at https://direct.mit.edu/dint/pages/submission-guidelines. Questions about how to submit and editorial process, please contact editorial office of Data Intelligence journal at data@mail.las.ac.cn.

DI专辑

Special Issue on Knowledge Graph for Social Good 

This special issue at Data Intelligence Journal aims to establish a bridge for researchers from industry and academia who are working on positive social impact in accordance with priorities outlined in the Sustainable Development Goals(SDGs). Contributions are invited in applying knowledge graphs (and related methodologies) relating to any of the SDGs and related topics. The special issue will show how businesses, social scientists, the public sector and academia use knowledge graphs to have a positive social impact. The efforts include various kinds of problems they are solving, bottlenecks they have, and insights they are gathering.

The topics include, but are not limited to:

  •  Efforts such as the International Aid Transparency (https://iatistandard.org/en/), Open Contracting (https://www.open-contracting.org/), and Open Corporates (https://opencorporates.com/) try to connect the dots between funds and registered entities.

  • The SDGs, related datasets and relevant news articles can be represented as a massive semantic graph. It is a great use-case for knowledge graphs – as a semantic layer on top of existing data will help map relationships between different SDGs and understand the interaction as well as overlap between target concepts.

  • Efforts to help on the social healthcare crisis such as Covid-19 and identification of social determinant of health using knowledge graphs.

 

Deadline

Submission deadline: September 30, 2021. Papers submitted before the deadline will be reviewed upon receipt.

 

Guest editors

The guest editors can be reached at vivek.a.khetan@accenture.com.

 

Guest editorial board

Lambert Hogenhout, the United NationsSecretariat

Vivek Khetan, Accenture Labs

Bogdan Sacaleanu, Accenture Labs

Rayid Ghani, Accenture Labs

 

Author Guidelines

Submissions shall be made through the ScholarOne systemat https://mc03.manuscriptcentral.com/di. Prospective authors must take notice of the submission guidelines posted at https://direct.mit.edu/dint/pages/submission-guidelines. Questions about how to submit and editorial process, please contact editorial office of Data Intelligence journal at data@mail.las.ac.cn.

 


 

OpenKG

开放知识图谱(简称 OpenKG)旨在促进中文知识图谱数据的开放与互联,促进知识图谱和语义技术的普及和广泛应用。

点击阅读原文,进入 OpenKG 网站。

转载地址:http://pesli.baihongyu.com/

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