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Discovering and disambiguating named entities in text

Johannes Hoffart
2013 Proceedings of the 2013 Sigmod/PODS Ph.D. symposium on PhD symposium - SIGMOD'13 PhD Symposium  
The first contribution is a robust disambiguation method using a graph algorithm that makes use of the coherence among entities in the input.  ...  A key challenge is the ambiguity of entity names, requiring robust methods to disambiguate names to canonical entities registered in a knowledge base.  ...  The TagMe system by Ferragina and Scaiella [FS12] uses very light-weight features, combining only the prior probability of an entity given a mention with the semantic relatedness of all candidate entities  ... 
doi:10.1145/2483574.2483582 dblp:conf/sigmod/Hoffart13 fatcat:bjqq5uusrragdm7ewraf63of4e

Towards Comprehensive Clinical Abbreviation Disambiguation Using Machine-Labeled Training Data

Gregory P Finley, Serguei V S Pakhomov, Reed McEwan, Genevieve B Melton
2017 AMIA Annual Symposium Proceedings  
Our tests demonstrate that semi-supervised abbreviation disambiguation is a viable and extensible option for medical NLP systems.  ...  Abbreviation disambiguation in clinical texts is a problem handled well by fully supervised machine learning methods.  ...  Acknowledgments The National Institutes of Health through the National Library of Medicine (R01LM011364 and R01GM102282), Clinical and Translational Science Award (8UL1TR000114-02), UMN Academic Health  ... 
pmid:28269852 pmcid:PMC5333249 fatcat:h7rlskbr3fd4djxpb22pdmhkt4

Improving Broad-Coverage Medical Entity Linking with Semantic Type Prediction and Large-Scale Datasets

Shikhar Vashishth, Denis Newman-Griffis, Rishabh Joshi, Ritam Dutt, Carolyn P. Rosé
2021 Journal of Biomedical Informatics  
Biomedical natural language processing tools are increasingly being applied for broad-coverage information extraction-extracting medical information of all types in a scientific document or a clinical  ...  All toolkits adopt a staged approach of mention detection followed by two stages of medical entity linking: (1) generating a list of candidate concepts, and (2) picking the best concept among them.  ...  concepts a specific mention may refer to-and disambiguation-picking the best candidate concept for the observed mention based on the context (includes both word and phrase sense disambiguation, or WSD  ... 
doi:10.1016/j.jbi.2021.103880 pmid:34390853 pmcid:PMC8952339 fatcat:ufxptrtdq5akzeeoarh6urgqci

Word Sense Disambiguation: Survey Study

Ahmed H. Aliwy, Hawraa A. Taher
2019 Journal of Computer Science  
The process of identifying the correct sense of a given word in a particular sentence is called Word Sense Disambiguation (WSD).  ...  From this work, it was concluded that (i) some methods give high accuracy for language but low for other, (ii) the size of the used data set affects the performance of the used algorithm, (iii) some of  ...  Acknowledgement The authors would like to thank the reviewers for their valuable comments and suggestions that contributed to the improvement of this work.  ... 
doi:10.3844/jcssp.2019.1004.1011 fatcat:zc5zwsoltzgvtjazqc2ayuheje

Theory of signs and statistical approach to big data in assessing the relevance of clinical biomarkers of inflammation and oxidative stress

Pietro Ghezzi, Kevin Davies, Aidan Delaney, Luciano Floridi
2018 Proceedings of the National Academy of Sciences of the United States of America  
The linguist Ferdinand de Saussure saw the language as a system of signs, where signs are related to other signs within the system, which led him to develop the concept that signs have a meaning (signification  ...  Graph edges with a weight of 1 indicate a strong attraction between the vertices, whereas graph edges with a weight of 0 indicate no attraction between the vertices.  ... 
doi:10.1073/pnas.1719807115 pmid:29463702 fatcat:wdddqyuojfbxjnldxdipd63olq

Knowledge-based personalized search engine for the Web-based Human Musculoskeletal System Resources (HMSR) in biomechanics

Tien Tuan Dao, Tuan Nha Hoang, Xuan Hien Ta, Marie Christine Ho Ba Tho
2013 Journal of Biomedical Informatics  
Human musculoskeletal system resources of the human body are valuable for the learning and medical purposes.  ...  Functional comparison between our knowledge-based search engine, a conventional search engine and a semantic search engine showed the originality and the robustness of our knowledge-based personalized  ...  Acknowledgments The authors would like to thank the anonymous reviewers for their comments leading to improve this paper. The present work was funded by the Picardie Region.  ... 
doi:10.1016/j.jbi.2012.11.001 pmid:23149160 fatcat:uns2nscgcffsncczjye2qt454m

Jointly Embedding Entities and Text with Distant Supervision

Denis Newman-Griffis, Albert M Lai, Eric Fosler-Lussier
2018 Proceedings of The Third Workshop on Representation Learning for NLP  
Learning representations for knowledge base entities and concepts is becoming increasingly important for NLP applications.  ...  We present a distantly-supervised method for jointly learning embeddings of entities and text from an unnanotated corpus, using only a list of mappings between entities and surface forms.  ...  Acknowledgments We would like to thank Chaitanya Shivade for helpful discussions, and all of our anonymous reviewers for their invaluable advice.  ... 
doi:10.18653/v1/w18-3026 dblp:conf/rep4nlp/Newman-GriffisL18 fatcat:uu3rtn4z2bhfvgpfosebqwm4qq

Jointly Embedding Entities and Text with Distant Supervision [article]

Denis Newman-Griffis, Albert M. Lai, Eric Fosler-Lussier
2018 arXiv   pre-print
Learning representations for knowledge base entities and concepts is becoming increasingly important for NLP applications.  ...  We present a distantly-supervised method for jointly learning embeddings of entities and text from an unnanotated corpus, using only a list of mappings between entities and surface forms.  ...  Acknowledgments We would like to thank Chaitanya Shivade for helpful discussions, and all of our anonymous reviewers for their invaluable advice.  ... 
arXiv:1807.03399v1 fatcat:setxblxdmbca7elf54hawhb3iy

Systematic Establishment of Robustness and Standards in Patient-Derived Xenograft Experiments and Analysis

Yvonne A. Evrard, Anuj Srivastava, Jelena Randjelovic, NCI PDXNet Consortium, James H. Doroshow, Dennis A. Dean, Jeffrey S. Morris, Jeffrey H Chuang
2020 Cancer Research  
In addition, we share the range of experimental procedures that maintained robustness, as well as standardized cloud-based workflows for PDX exome-seq and RNA-Seq analysis and for evaluating growth.  ...  To determine the robustness of PDX studies, the PDXNet tested temozolomide drug response for three pre-validated PDX models (sensitive, resistant, and intermediate) across four blinded PDX Development  ...  Authors' Contributions Conception and design: Y.A. Evrard  ... 
doi:10.1158/0008-5472.can-19-3101 pmid:32152150 pmcid:PMC7272270 fatcat:duhkmav5zjbdnibfjzisyf7elm

Survey on challenges of Question Answering in the Semantic Web

Konrad Höffner, Sebastian Walter, Edgard Marx, Ricardo Usbeck, Jens Lehmann, Axel-Cyrille Ngonga Ngomo, Marta Sabou
2017 Semantic Web Journal  
We identify common challenges, structure solutions, and provide recommendations for future systems.  ...  Semantic Question Answering (SQA) removes two major access requirements to the Semantic Web: the mastery of a formal query language like SPARQL and knowledge of a specific vocabulary.  ...  The vector space over the set of terms in the corpus is used to create a distributional vector space based on the weighted term vectors for each concept.  ... 
doi:10.3233/sw-160247 fatcat:lzlupslbqbcbnlayqi7uy4ok2e

Author Name Disambiguation in MEDLINE

Vetle I Torvik, Neil R Smalheiser
2009 ACM Transactions on Knowledge Discovery from Data  
unbiased training sets; (c) new methods for estimating the prior probability; (d) a weighted least squares algorithm for correcting transitivity violations; and (e) a maximum likelihood based agglomerative  ...  Here we test the hypothesis that the Author-ity model will suffice to disambiguate author names for the vast majority of articles in MEDLINE.  ...  Acknowledgments We sincerely thank Wei Zhang for programming assistance, Clement Yu for advice on computational issues, and Jeff Baer for permission to use Community of Science data.  ... 
pmid:20072710 pmcid:PMC2805000 fatcat:iy6qajnpyrh7ddmw2i3srlimfy

Recent advances in methods of lexical semantic relatedness – a survey

ZIQI ZHANG, ANNA LISA GENTILE, FABIO CIRAVEGNA
2012 Natural Language Engineering  
DEDICATION This thesis is dedicated to my brilliant wife, Yaxin Liu, for her infinite love and support throughout the course of this work.  ...  Resolving ambiguity concerns recognising the true referent entity of a name reference, essentially a further named entity 'recognition' step and often a compulsory pro-VI  ...  Each concept then receives a weight that represents the importance of the concept to the webpage to be disambiguated.  ... 
doi:10.1017/s1351324912000125 fatcat:b62qbqwrqfaf3gytw22yktc5ae

Generic Information Can Retrieve Known Biological Associations: Implications for Biomedical Knowledge Discovery

Herman H. H. B. M. van Haagen, Peter A. C. 't Hoen, Barend Mons, Erik A. Schultes, Eduardo G. Altmann
2013 PLoS ONE  
Here, we attempted to optimize the retrieval performance for protein-protein interactions (PPI) by filtering generic concepts (node filtering) or links to generic concepts (edge filtering) from a weighted  ...  For instance the concept "binding" is indicative for PPI retrieval and the concept "mutation abnormality" is indicative for gene-disease associations.  ...  A concept must occur in a minimum of 5 abstracts before a concept profile is created [9] . The weight w ij for a concept j in this profile indicates the strength of its association to the concept i.  ... 
doi:10.1371/journal.pone.0078665 pmid:24260124 pmcid:PMC3834066 fatcat:7nt7kzypbngmrmiicfygpxrbvu

Author name disambiguation in MEDLINE

Vetle I. Torvik, Neil R. Smalheiser
2009 ACM Transactions on Knowledge Discovery from Data  
ACKNOWLEDGMENTS We sincerely thank Wei Zhang for programming assistance, Clement Yu for advice on computational issues, and Jeff Baer for permission to use Community of Science data.  ...  We also thank the US National Library of Medicine (NLM) for providing the 2006 baseline release of MEDLINE.  ...  Each estimate p ij is weighted by the inverse of its variance, w ij = 1/(p ij (1−p ij )), and the weights for the estimates below 0.5 are reduced by a factor of 0.5.  ... 
doi:10.1145/1552303.1552304 fatcat:4vd5yjoccfdc7l4a2mqn6ypxti

Biomedical Interpretable Entity Representations [article]

Diego Garcia-Olano, Yasumasa Onoe, Ioana Baldini, Joydeep Ghosh, Byron C. Wallace, Kush R. Varshney
2021 arXiv   pre-print
In this paper, we create a new entity type system and training set from a large corpus of biomedical texts by mapping entities to concepts in a medical ontology, and from these to Wikipedia pages whose  ...  We show that BIERs achieve strong performance in biomedical tasks including named entity disambiguation and entity label classification, and we provide error analysis to highlight the utility of their  ...  Hence for this mention and context from a BIER PubMed abstract, we are able to extract a (mention, context, list of types) triple of the form (“phase II clinical trial”, context, [“Clinical research  ... 
arXiv:2106.09502v1 fatcat:irdxjdgzb5bxvd232urlithh7u
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