topic page so that developers can more easily learn about it.
A lot of the citations place the current work in context. Tobias Weber. ", An Information Retrieval system for searching research publications, papers or articles using Apache Solr, repository of scripts used to ingest data into DELVE system at KAUST.
Open Data License: ODC-BY A few citations are used to "prove" something is (ir)relevant for the current experiments. Due to COVID-19, the whole event (including both conference and workshop) will be held online. Machine Learning, International Council for Machinery Lubrication. Instead, it should nudge your beliefs slightly one way or another. The website is very long to load, its a bit of a shame. -> Paper Y is false. "This data set is generated by linking two large academic graphs: Microsoft Academic Graph (MAG) and AMiner.
Short Paper - A Philological Perspective on Meta-Scientific Knowledge Graphs.
Nothing loaded. Although we cited sixty-odd papers, I don't think our conclusions critically depends on any one of them. SKGs focus on the scholarly domain and describe the actors (e.g., authors, organizations), the documents (e.g., publications, patents), and the research knowledge (e.g., research topics, tasks, technologies) in this space as well as their reciprocal relationships. I'm looking forward to this working properly - is there anything I can do to help debug/investigate? Data models (e.g., ontologies, vocabularies, schemas) for the description of scholarly data and the linking between scholarly data/software and academic papers that report or cite them, Description of citations for scholarly articles, data and software and their interrelationships, Applications for the (semi-)automatic annotation of scholarly papers, Theoretical models describing the rhetorical and argumentative structure of scholarly papers and their application in practice, Methods for quality assessment of scientific knowledge graphs, Description and use of provenance information of scholarly data, Methods for the exploration, retrieval and visualization of scientific knowledge graphs, Scientific claims identification from textual contents, Automatic or semi-automatic approaches to making sense of research dynamics, Content- and data-based analysis on scholarly papers, Automatic semantic enhancement of existing scholarly libraries and papers, Reconstruction, forecasting and monitoring of scholarly data, Novel user interfaces for interaction with paper, metadata, content, software and data, Visualisation of related papers or data according to multiple dimensions (semantic similarity of abstracts, keywords, etc. Contact: skg2020@easychair.org, 1st Workshop on Scientific Knowledge Graphs, https://adbis-tpdl-eda-2020.insight-outside.fr/, https://easychair.org/conferences/?conf=skg2020. You signed in with another tab or window. papers that cited need to be re-examined at best. "if someday a paper is proved false, all underlying papers citing this one should be too". So paper X is published. If these papers turned out to be false, it might make the paper less "interesting"--the mechanism underlying a useless therapy is pretty boring, after all--but the factual content would be unchanged.