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Construction of the Literature Graph in Semantic Scholar

Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula, Iz Beltagy, Miles Crawford, Doug Downey, Jason Dunkelberger, Ahmed Elgohary, Sergey Feldman, Vu Ha, Rodney Kinney, Sebastian Kohlmeier (+11 others)
2018 Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers)  
The resulting literature graph consists of more than 280M nodes, representing papers, authors, entities and various interactions between them (e.g., authorships, citations, entity mentions).  ...  We describe a deployed scalable system for organizing published scientific literature into a heterogeneous graph to facilitate algorithmic manipulation and discovery.  ...  Grounding the entity mentions in a manually-curated KB also increases user confidence in automated predictions.  ... 
doi:10.18653/v1/n18-3011 dblp:conf/naacl/AmmarGBBCDDEFHK18 fatcat:xxegd6v66jhynhjeqv3qgztrfm

Construction of the Literature Graph in Semantic Scholar [article]

Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula, Iz Beltagy, Miles Crawford, Doug Downey, Jason Dunkelberger, Ahmed Elgohary, Sergey Feldman, Vu Ha, Rodney Kinney, Sebastian Kohlmeier (+9 others)
2018 arXiv   pre-print
The resulting literature graph consists of more than 280M nodes, representing papers, authors, entities and various interactions between them (e.g., authorships, citations, entity mentions).  ...  We describe a deployed scalable system for organizing published scientific literature into a heterogeneous graph to facilitate algorithmic manipulation and discovery.  ...  Grounding the entity mentions in a manually-curated KB also increases user confidence in automated predictions.  ... 
arXiv:1805.02262v1 fatcat:v5vsjnzs2nfulk4iq3g2pisp6m

Life-iNet: A Structured Network-Based Knowledge Exploration and Analytics System for Life Sciences

Xiang Ren, Jiaming Shen, Meng Qu, Xuan Wang, Zeqiu Wu, Qi Zhu, Meng Jiang, Fangbo Tao, Saurabh Sinha, David Liem, Peipei Ping, Richard Weinshilboum (+1 others)
2017 Proceedings of ACL 2017, System Demonstrations  
Search engines running on scientific literature have been widely used by life scientists to find publications related to their research.  ...  It also provides functionalities for finding distinctive entities for given entity types, and generating hypothetical facts to assist literaturebased knowledge discovery (e.g., drug target prediction).  ...  Acknowledgement Research was sponsored in part by the U.S. Army Research Lab. under Cooperative Agreement No.  ... 
doi:10.18653/v1/p17-4010 dblp:conf/acl/RenSQWWZJTSLPWH17 fatcat:l4imv6rw6zeqzaxsroze3i4g4u

Extracting a Knowledge Base of Mechanisms from COVID-19 Papers [article]

Tom Hope, Aida Amini, David Wadden, Madeleine van Zuylen, Sravanthi Parasa, Eric Horvitz, Daniel Weld, Roy Schwartz, Hannaneh Hajishirzi
2021 arXiv   pre-print
Our experiments demonstrate the utility of our KB in supporting interdisciplinary scientific search over COVID-19 literature, outperforming the prominent PubMed search in a study with clinical experts.  ...  The COVID-19 pandemic has spawned a diverse body of scientific literature that is challenging to navigate, stimulating interest in automated tools to help find useful knowledge.  ...  Given a boolean span matching function m(s 1 , s 2 ) = 1(s 1 matches s 2 ), a predicted entity mentionê is correctly identified if there exists some gold mention e * in D such that m(ê, e * ) = 1 (since  ... 
arXiv:2010.03824v3 fatcat:zibxa5i2j5bh5engtlv44eifhq

TaxoNERD: deep neural models for the recognition of taxonomic entities in the ecological and evolutionary literature [article]

Nicolas Le Guillarme, Wilfried Thuiller
2021 bioRxiv   pre-print
Given the biodiversity crisis, we more than ever need to access information on multiple taxa (e.g. distribution, traits, diet) in the scientific literature to understand, map and predict all-inclusive  ...  A prerequisite is the ability to recognise mentions of taxa in text, a special case of named entity recognition (NER).  ...  of the predicted entity (see Fig. 6 ).  ... 
doi:10.1101/2021.06.08.444426 fatcat:l2epu7suznc4taiknapvf73j44

NTNU at SemEval-2018 Task 7: Classifier Ensembling for Semantic Relation Identification and Classification in Scientific Papers

Biswanath Barik, Utpal Kumar Sikdar, Björn Gambäck
2018 Proceedings of The 12th International Workshop on Semantic Evaluation  
For relation identification and classification in subtask 2, it achieved F 1 scores of 33.9% and 17.0%,  ...  The best setting achieved F 1 scores of 47.4% and 66.0% in the relation classification subtasks 1.1 and 1.2.  ...  Inputs to brat annotation: The input training and test files are in xml format with the entity mentions marked. Each entity mention has an ID with two parts, abstract ID and entity number.  ... 
doi:10.18653/v1/s18-1138 dblp:conf/semeval/BarikSG18 fatcat:nuwk5lcy2rccjgfzjt5pfc5hdm

Low Resource Recognition and Linking of Biomedical Concepts from a Large Ontology [article]

Sunil Mohan and Rico Angell and Nick Monath and Andrew McCallum
2021 arXiv   pre-print
Tools to explore scientific literature are essential for scientists, especially in biomedicine, where about a million new papers are published every year.  ...  In this paper, we develop a new model that overcomes these challenges by (1) generalizing to entities unseen at training time, and (2) incorporating linking predictions into the mention segmentation decisions  ...  To build such a semantic index, entity mentions must be recognized and linked in the text of scientific papers.  ... 
arXiv:2101.10587v2 fatcat:ojir5owtifd4zkmcpwrfobnl6q

A hybrid approach for automated mutation annotation of the extended human mutation landscape in scientific literature

Antonio Jimeno Yepes, Andrew MacKinlay, Natalie Gunn, Christine Schieber, Noel Faux, Matthew Downton, Benjamin Goudey, Richard L Martin
2018 AMIA Annual Symposium Proceedings  
However, information about such mutations is typically first made available in the scientific literature, and is then later manually curated into more standardized genomic databases.  ...  Detecting mutations in the literature is the first key step towards automating this process.  ...  in the scientific literature.  ... 
pmid:30815103 pmcid:PMC6371299 fatcat:u5q5labhtvgi3drzr4pqjsmygy

End-to-End NLP Knowledge Graph Construction [article]

Ishani Mondal, Yufang Hou, Charles Jochim
2021 arXiv   pre-print
This paper studies the end-to-end construction of an NLP Knowledge Graph (KG) from scientific papers.  ...  focus on extracting four types of relations: evaluatedOn between tasks and datasets, evaluatedBy between tasks and evaluation metrics, as well as coreferent and related relations between the same type of entities  ...  Related Work There is a wealth of research in the NLP community on extracting information from scientific literature.  ... 
arXiv:2106.01167v1 fatcat:stieiqm3djf5ffy4kky7jup55i

A hybrid approach for automated mutation annotation of the extended human mutation landscape in scientific literature [article]

Antonio Jimeno Yepes, Andrew MacKinlay, Natalie Gunn, Christine Schieber, Noel Faux, Matthew Downton, Benjamin Goudey, Richard L Martin
2018 bioRxiv   pre-print
However, information about such mutations is typically first made available in the scientific literature, and is then later manually curated into more standardized genomic databases.  ...  Detecting mutations in the literature is the first key step towards automating this process.  ...  in the scientific literature.  ... 
doi:10.1101/363473 fatcat:ic4iss7rpfaizgea46e5caworq

Integrated protein function prediction by mining function associations, sequences, and protein–protein and gene–gene interaction networks

Renzhi Cao, Jianlin Cheng
2016 Methods  
The mentioning of gene names in the body of the scientific literature 1901-2017 and their fractional counting is used as a proxy to assess the level of biological function discovery.  ...  The protein function discovery rate measured as numbers of proteins first mentioned or crossing a threshold of accumulated FPEs in a given year has grown until 2000 but is in decline thereafter.  ...  Another 2500 named entities have been mentioned in the life science literature at various levels of scrutiny.  ... 
doi:10.1016/j.ymeth.2015.09.011 pmid:26370280 pmcid:PMC4894840 fatcat:enov227z3bdnnakh2lfmne3uci

CitationIE: Leveraging the Citation Graph for Scientific Information Extraction [article]

Vijay Viswanathan, Graham Neubig, Pengfei Liu
2021 arXiv   pre-print
place in the broader literature.  ...  Prior work has considered extracting document-level entity clusters and relations end-to-end from raw scientific text, which can improve literature search and help identify methods and materials for a  ...  We ensure the mention identification step does not predict entities in citance sections, which would lead to false positive entities in downstream tasks.  ... 
arXiv:2106.01560v1 fatcat:jruehl7r2beodcqrpddtwl3fs4

Predicting the impact of scientific concepts using full-text features

Kathy McKeown, Hal Daume, Snigdha Chaturvedi, John Paparrizos, Kapil Thadani, Pablo Barrio, Or Biran, Suvarna Bothe, Michael Collins, Kenneth R. Fleischmann, Luis Gravano, Rahul Jha (+8 others)
2016 Journal of the Association for Information Science and Technology  
New scientific concepts, interpreted broadly, are continuously introduced in the literature, but relatively few concepts have a long-term impact on society.  ...  The identification of such concepts is a challenging prediction task that would help multiple parties-including researchers and the general public-focus their attention within the vast scientific literature  ...  In contrast, by examining scientific articles related to rewiring in the same time period, our system predicts that this term will not be prominent in scientific articles published in 2004-2007.  ... 
doi:10.1002/asi.23612 fatcat:rebcnah2ozgflamayrfcr7b52y

A corpus for differential diagnosis: an eye diseases use case [article]

Antonio Jimeno Yepes, David Martinez Iraola, Pieter Barnard, Tinu Joy
2021 bioRxiv   pre-print
We have created a corpus for the extraction of information related to diagnosis from scientific literature focused on eye diseases.  ...  The corpus that we have developed is publicly available, thus the scientific community is able to reproduce our work and reuse the corpus in their work.  ...  We would like to thank Alexa Moses 395 for her support and help in releasing the data set.  ... 
doi:10.1101/2021.05.10.443343 fatcat:ua53q4yemzctvgqkz4qdscllqe

Predicting Emerging Themes in Rapidly Expanding COVID-19 Literature with Dynamic Word Embedding Networks and Machine Learning [article]

Ridam Pal, Harshita Chopra, Raghav Awasthi, Harsh Bandhey, Aditya Nagori, Amogh Gulati, Ponnurangam Kumaraguru, Tavpritesh Sethi
2021 medRxiv   pre-print
Conclusion: We provide an explainable AI approach for querying, tracking and predicting novel insights in COVID-19 peer reviewed literature.  ...  Since peer-reviewed research is a trusted source of evidence, capturing and predicting the emerging themes in COVID-19 literature are crucial for guiding research and policy.  ...  We also acknowledge support from the Center of Excellence in Healthcare and the Center of Excellence in Artificial Intelligence at IIIT-Delhi.  ... 
doi:10.1101/2021.01.14.21249855 fatcat:zpa4evfpbbbehpc7rumnwy266q
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