征稿 | Call for papers on Knowledge Graphs
Knowledge graph是Data Intelligence的核心主題和期刊特色之一。為持續(xù)展示這一領(lǐng)域的最新進(jìn)展和前沿成果,Data Intelligence正在與國際學(xué)者一道策劃兩期Knowledge graph專輯。
期待大家關(guān)注并積極投稿參與!
DI專輯
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.
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Topics relevant to this special issue include, but are not limited to, the following:
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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.
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Deadline
Submission deadline: September 30, 2021. Papers submitted before the deadline will be reviewed upon receipt.
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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
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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專輯
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.
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Deadline
Submission deadline: September 30, 2021. Papers submitted before the deadline will be reviewed upon receipt.
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Guest editors
The guest editors can be reached at vivek.a.khetan@accenture.com.
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Guest editorial board
Lambert Hogenhout, the United NationsSecretariat
Vivek Khetan, Accenture Labs
Bogdan Sacaleanu, Accenture Labs
Rayid Ghani, Accenture Labs
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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.
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OpenKG
開放知識圖譜(簡稱 OpenKG)旨在促進(jìn)中文知識圖譜數(shù)據(jù)的開放與互聯(lián),促進(jìn)知識圖譜和語義技術(shù)的普及和廣泛應(yīng)用。
點(diǎn)擊閱讀原文,進(jìn)入 OpenKG 網(wǎng)站。
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