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Bisila, Jonathan

Publications and source records attributed to Bisila, Jonathan.

6 records
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DOE OSTI2022

For the Public Good: Connecting, Retaining, and Recognizing Current and Future RSEs at U.S. National Research Laboratories and Agencies

U.S. national research laboratories and agencies play an integral role in advancing science and technology for the public good. The authors of this article, as research software engineers (RSEs) and allies from eight unique national R&D organizations, came together to explore RSE needs from the perspective of national institutions. We identified three key areas of improvement for future RSEs to pursue science in the national interest: community establishment, hiring and retention, and recognition. In conclusion, to retain and cultivate this essential talent, U.S. national institutions must evolve to support appropriate career pathways for RSEs, and to recognize and reward RSEs’ work.

42 ENGINEERING↗
DOE OSTI2021

Relationship Extraction: Automatic Information Extraction and Organization for Supporting Analysts in Threat Assessment

In order for analysts to be able to do their work, they sift through hundreds, thousands, or even millions of documents to make connections between entities of interest. This process is time consuming, tedious, and prone to potential error from missed connections or connections made that should not have been. There exist many tools in natural language processing, or NLP, to extract information from documents. However, when it comes to relationship extraction, there has been varied success. This project began with a goal to solve the relationship extraction problem which developed into a deeper understanding of the problem and the associated challenges for solving this problem on a general scale. In this report, we explain our research and approach to relationship extraction, identify other auxiliary problems in NLP that provide additional challenges to solving relationship extraction generally, explain our analysis of the current state of relationship extraction, and postulate future work to address these problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Survey of Current State of the Art Entity-Relation Extraction Tools

In the area of information extraction from text data, there exists a number of tools with the capability of extracting entities, topics, and their relationships with one another from both structured and unstructured text sources. Such information has endless uses in a number of domains, however, the solutions to getting this information are still in early stages and has room for improvement. The topic has been explored from a research perspective by academic institutions, as well as formal tool creation from corporations but has not made much advancement since the early 2000's. Overall, entity extraction, and the related topic of entity linking, is common among these tools, though with varying degrees of accuracy, while relationship extraction is more difficult to find and seems limited to same sentence analysis. In this report, we take a look at the top state of the art tools currently available and identify their capabilities, strengths, and weaknesses. We explore the common algorithms in the successful approaches to entity extraction and their ability to efficiently handle both structured and unstructured text data. Finally, we highlight some of the common issues among these tools and summarize the current ability to extract relationship information.

97 MATHEMATICS AND COMPUTING↗