Papers by Denis Newman-Griffis
Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network (2021.acl-long)
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| Challenge: | Knowledge graphs (KGs) are incomplete because of the large number of benchmark datasets that are not representative of real KGs. |
| Approach: | They develop a deep convolutional network that utilizes textual entity representations to distill the knowledge from the convolution into a student network that re-ranks promising candidate entities. |
| Outcome: | The proposed model outperforms recent methods in a realistic setting where dense connectivity is not guaranteed. |
Writing habits and telltale neighbors: analyzing clinical concept usage patterns with sublanguage embeddings (D19-62)
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| Challenge: | Existing biomedical concepts may have multiple, often non-compositional surface forms, making them difficult to analyze using lexical occurrence alone. |
| Approach: | They propose a method for characterizing usage patterns of clinical concepts among different document types by embedding concepts on clinical documents of different types and measuring their nearest neighborhood structures. |
| Outcome: | Experiments on the MIMIC-III corpus show that the proposed method captures clinically relevant differences in concept usage while correcting for noise in embedding learning. |
HARE: a Flexible Highlighting Annotator for Ranking and Exploration (D19-3)
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| Challenge: | Using NLP techniques to analyze new information domains is challenging, authors report . authors demonstrate use of HARE to rank documents based on their relevance to mobility . |
| Approach: | They propose a system for highlighting relevant information in document collections to support ranking and triage. |
| Outcome: | The proposed system can be used to rank and explore documents in clinical data . it provides tools for post-processing and qualitative analysis for model development and tuning. |
Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research (2021.naacl-main)
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| Challenge: | Natural language processing research is often assumed to emerge naturally . many innovations go unapplied and important questions remain unstudied . |
| Approach: | They propose a new paradigm to structure and facilitate the processes by which basic and applied NLP research inform one another. |
| Outcome: | The proposed framework provides a roadmap for developing Translational NLP as a dedicated research area. |
TextEssence: A Tool for Interactive Analysis of Semantic Shifts Between Corpora (2021.naacl-demos)
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| Challenge: | Existing studies using distributional embeddings to study language use have focused on quantitative measurement of change, rather than inter-corpus analysis. |
| Approach: | They propose a system that allows comparative analysis of corpora using embeddings. |
| Outcome: | The proposed system can be used for categorical and comparative analysis of text corpora. |