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CORD-19: The COVID-19 Open Research Dataset
The mechanics of dataset construction are described, highlighting challenges and key design decisions, an overview of how CORD-19 has been used, and several shared tasks built around the dataset are described.
WSDM Cup 2016: Entity Ranking Challenge
In this paper, we describe the WSDM Cup entity ranking challenge held in conjunction with the 2016 Web Search and Data Mining conference (WSDM 2016). Participants in the challenge were provided…
Word add-in for ontology recognition: semantic enrichment of scientific literature
The Word add-in for ontology term recognition makes it possible for an author to add semantic data to a document as it is being written and it encodes these data using XML tags that are effectively a standard in life sciences literature.
The rise of the machines: Artificial intelligence meets scholarly content
Key points New forms of human/machine dialogue are emerging as robots understand vast amounts of content rather than simply indexing content as strings of characters. Recognizing strings of…
Interactive Multi-Submission Deposit Workflows for Desktop Applications
This paper proposes a solution that embeds the workflow for multiple submissions into the desktop application of the author, most commonly Microsoft Word, and extends the work done on the Microsoft Word Author Add-in tool to allow two-way negotiation between each repository and thedesktop application.
Rich Search and Discovery for Research Datasets: Building the Next Generation of Scholarly Infrastructure
Enhancing research publications using Rich Interactive Narratives
- Kenji Takeda, G. Earl, J. Frey, S. Keay, Alex D Wade
- Computer SciencePhilosophical Transactions of the Royal Society A…
- 28 January 2013
The application of the Rich Interactive Narrative framework is described to provide such a mechanism in the fields of archaeology and chemistry, to supplement academic journal papers, and includes an extensive authoring tool for deployment to the Web.
Personalized Feed/Query-formulation, Predictive Impact, and Ranking
Meta’s approach to query formulation and ranking to improve retrieval of recently published, and yet un-cited academic publications is discussed.