Papers by Kuansan Wang

3 papers
Explainable and Sparse Representations of Academic Articles for Knowledge Exploration (2020.coling-main)

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Challenge: a system for summarizing academic articles by concept tagging has shown great coverage and high accuracy of concept identification.
Approach: They propose to transform tagged concepts into sparse vectors as representations of academic documents.
Outcome: The proposed system can be applied to a broader class of applications.
SciConceptMiner: A system for large-scale scientific concept discovery (2021.acl-demo)

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Challenge: SciConceptMiner is a self-supervised system for the capture of scientific concepts . the system is scalable to the size of documents and the number of topics it can model .
Approach: They propose a self-supervised system for the automatic capture of scientific concepts from academic publications and semi-structured data.
Outcome: The proposed system achieves high accuracy (94.7%) with more than 740K scientific concepts.
A Web-scale system for scientific knowledge exploration (P18-4)

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Challenge: a system that organizes scientific knowledge into a hierarchical concept structure is needed to enable efficient exploration of Web-scale knowledge.
Approach: They propose a system that organizes scientific knowledge into a hierarchical concept structure . system allows researchers to identify hundreds of thousands of scientific concepts . it also allows researchers tagging scientific publications into millions of concepts based on text and graph structure based model .
Outcome: The proposed system builds the most comprehensive cross-domain scientific concept ontology published to date, with more than 200 thousand concepts and over one million relationships.

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