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    • Roussinov, Dmitri (6)
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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Predicting Clinical Events Based on Raw Text: From Bag-of-Words to Attention-Based Transformers Roussinov, Dmitri; Conkie, Andrew; Patterson, Andrew... In: Front Digit Health (2022) BASE Show details 2 Predicting clinical events based on raw text : from bag-of-words to attention-based transformers Roussinov, Dmitri; Conkie, Andrew; Patterson, Andrew. - 2022 BASE Show details 3 Recognizing semantic relations by combining transformers and fully connected models Roussinov, Dmitri; Sharoff, Serge; Puchnina, Nadezhda. - : European Language Resources Association (ELRA), 2020 Abstract: Automatically recognizing an existing semantic relation (e.g. "is a", "part of", "property of", "opposite of" etc.) between two words (phrases, concepts, etc.) is an important task affecting many NLP applications and has been subject of extensive experimentation and modeling. Current approaches to automatically telling if a relation exists between two given concepts X and Y can be grouped into two types: 1) those modeling word-paths connecting X and Y in text and 2) those modeling distributional properties of X and Y separately, not necessary in the proximity to each other. Here, we investigate how both types can be improved and combined. We suggest a distributional approach that is based on an attention-based transformer. We have also developed a novel word path model that combines useful properties of a convolutional network with a fully connected language model. While our transformer-based approach works better, both our models significantly outperform the state-of-the-art within their classes of approaches. We also demonstrate that combining the two approaches results in additional gains since they use somewhat different data sources. Keyword: Philology. Linguistics URL: https://strathprints.strath.ac.uk/75898/1/Roussinov_etal_LREC_2021_Recognizing_semantic_relations_by_combining_transformers_and_fully_connected_models.pdf https://strathprints.strath.ac.uk/75898/ https://www.aclweb.org/anthology/2020.lrec-1.715/ BASE Hide details 4 Detecting word substitutions in text Fong, SeWong; Roussinov, Dmitri; Skillicorn, David. - 2008 BASE Show details 5 Building on Redundancy: Factoid Question Answering, Robust Retrieval and the “Other” Roussinov, Dmitri; Chau, Micheal; Filatova, Elena. - : Proceedings of TREC 2005, 2005 BASE Show details 6 Building on Redundancy: Factoid Question Answering, Robust Retrieval and the “Other” ... Roussinov, Dmitri; Chau, Micheal; Filatova, Elena. - : Columbia University, 2005 BASE Show details

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