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Natural Language Processing for Information Extraction [article]

Sonit Singh
2018 arXiv   pre-print
Various sub-tasks of IE such as Named Entity Recognition, Coreference Resolution, Named Entity Linking, Relation Extraction, Knowledge Base reasoning forms the building blocks of various high end Natural  ...  Much of this data lies in unstructured form and manually managing and effectively making use of it is tedious, boring and labor intensive.  ...  Although, Named Entity Recognition (NER), Coreference Resolution (CR), Cross-Document Coreference Resolution (CCR), and Named Entity Linking (NEL) involve close relations but they were not explored jointly  ... 
arXiv:1807.02383v1 fatcat:3bdyidbjp5hn7c2w4iqve4ajvi

On Difficulties of Cross-Lingual Transfer with Order Differences: A Case Study on Dependency Parsing [article]

Wasi Uddin Ahmad, Zhisong Zhang, Xuezhe Ma, Eduard Hovy, Kai-Wei Chang, Nanyun Peng
2019 arXiv   pre-print
In this paper, we investigate cross-lingual transfer and posit that an order-agnostic model will perform better when transferring to distant foreign languages.  ...  The former relies on sequential information while the latter is more flexible at modeling word order.  ...  We are grateful for the Stanford NLP group's comments and feedback when we present the preliminary results in their seminar. We thank Graham Neubig and the  ... 
arXiv:1811.00570v3 fatcat:n47ecgxpxbcitaply4ykgpns4m

A Survey of Embedding Space Alignment Methods for Language and Knowledge Graphs [article]

Alexander Kalinowski, Yuan An
2020 arXiv   pre-print
Given the pervasive nature of these algorithms, the natural question becomes how to exploit the embedding spaces to map, or align, embeddings of different data sources.  ...  We provide a classification of the relevant alignment techniques and discuss benchmark datasets used in this field of research.  ...  In addition to cross-lingual knowledge graph datasets, several studies have split larger graphs into smaller components, each of which has linking entities that may be used as seeds to re-unify the graph  ... 
arXiv:2010.13688v1 fatcat:npkzwukih5gwnkvng2fxy7ls5y

Message from the general chair

Benjamin C. Lee
2015 2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)  
Learning-based Multi-Sieve Co-reference Resolution with Knowledge Lev Ratinov and Dan Roth Saturday 11:00am-11:30am -202 A (ICC) We explore the interplay of knowledge and structure in co-reference resolution  ...  To inject knowledge, we use a state-of-the-art system which cross-links (or "grounds") expressions in free text to Wikipedia.  ...  multi-lingual data with named entity tags.  ... 
doi:10.1109/ispass.2015.7095776 dblp:conf/ispass/Lee15 fatcat:ehbed6nl6barfgs6pzwcvwxria

Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases [article]

Gerhard Weikum, Luna Dong, Simon Razniewski, Fabian Suchanek
2021 arXiv   pre-print
To support the long-term life-cycle and the quality assurance of machine knowledge, the article presents methods for constructing open schemas and for knowledge curation.  ...  This machine knowledge can be harnessed to semantically interpret textual phrases in news, social media and web tables, and contributes to question answering, natural language processing and data analytics  ...  We are most grateful for the thoughtful and extremely helpful comments by Soumen Chakrabarti, AnHai Doan and two other (anonymous) reviewers.  ... 
arXiv:2009.11564v2 fatcat:vh2lqfmhhbcwpf6dcsej3hhvgy

Low-Resource Adaptation of Neural NLP Models [article]

Farhad Nooralahzadeh
2020 arXiv   pre-print
The objective of this thesis is to investigate methods for dealing with such low-resource scenarios in information extraction and natural language understanding.  ...  However, in real-world applications of NLP, the textual resources vary across several dimensions, such as language, dialect, topic, and genre.  ...  "MLQA: Evaluating Cross-lingual Extractive Question Answering". In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics.  ... 
arXiv:2011.04372v1 fatcat:626mbe5ba5bkdflv755o35u5pq

Semantic Relations and Deep Learning [article]

Vivi Nastase, Stan Szpakowicz
2021 arXiv   pre-print
A new Chapter 5 of the book, by Vivi Nastase and Stan Szpakowicz, discusses relation classification/extraction in the deep-learning paradigm which arose after the first edition appeared.  ...  The second edition of "Semantic Relations Between Nominals" by Vivi Nastase, Stan Szpakowicz, Preslav Nakov and Diarmuid \'O S\'eaghdha has been published in April 2021 by Morgan & Claypool (  ...  Many of the embedding methods supply pretrained word embeddings in a number of languages, or even cross-lingual data such as XLM [Conneau et al., 2019] .  ... 
arXiv:2009.05426v4 fatcat:rmzoalfwcza4nex7pd4u6w7kbe

Predicted selective increase of cortical magnification due to cortical folding [article]

Markus A. Dahlem, Jan Tusch
2012 arXiv   pre-print
The advantage of our tensor method over other surface-based 3D methods to explore cortical morphometry is that M expresses cortical quantities in the corresponding sensory space.  ...  Thus, the gain of surface area by cortical folding links anatomical structure to cortical function in a previously unrecognized way, which may guide sulci development.  ...  JT was supported by a grant of the Deutsche Forschungsgemeinschaft (DA-602/1-1); MAD acknowledges support by Deutsche Forschungsgemeinschaft in the framework of SFB910.  ... 
arXiv:1210.8415v1 fatcat:iafujynobraqfcx5zmf62zdyoa

Predicted Selective Increase of Cortical Magnification Due to Cortical Folding

Markus A Dahlem, Jan Tusch
2012 Journal of Mathematical Neuroscience  
The advantage of our tensor method over other surface-based 3D methods to explore cortical morphometry is that M expresses cortical quantities in the corresponding sensory space.  ...  Thus, the gain of surface area by cortical folding links anatomical structure to cortical function in a previously unrecognized way, which may guide sulci development.  ...  JT was supported by a grant of the Deutsche Forschungsgemeinschaft (DA-602/1-1); MAD acknowledges support by Deutsche Forschungsgemeinschaft in the framework of SFB910.  ... 
doi:10.1186/2190-8567-2-14 pmid:23245207 pmcid:PMC3571916 fatcat:2uuddwvlhbhzhnnvrwa2vhidgu

Systematic Review of Functional MRI Applications for Psychiatric Disease Subtyping

Lucas Miranda, Riya Paul, Benno Pütz, Nikolaos Koutsouleris, Bertram Müller-Myhsok
2021 Frontiers in Psychiatry  
This is particularly relevant for the field of personalized medicine, which searches for data-driven approaches to improve diagnosis, prognosis, and treatment selection for individual patients.Methods:  ...  Whereas results for all explored diseases are inconsistent, we believe this reflects the need for concerted, multisite data collection efforts with a strong focus on measuring the generalizability of results  ...  This yielded specific patterns of cortical thickness changes in the hippocampus, the lingual gyrus, the occipital face, and Wernicke's areas for different clusters, all previously linked to schizophrenia  ... 
doi:10.3389/fpsyt.2021.665536 pmid:34744805 pmcid:PMC8569315 fatcat:jmcxqcdzjba5bhvcpcrj2zvv3i

Graph Neural Networks for Natural Language Processing: A Survey [article]

Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long
2021 arXiv   pre-print
Deep learning has become the dominant approach in coping with various tasks in Natural LanguageProcessing (NLP).  ...  We further introducea large number of NLP applications that are exploiting the power of GNNs and summarize thecorresponding benchmark datasets, evaluation metrics, and open-source codes.  ...  between entity relations and co-reference links in the graph decoder.  ... 
arXiv:2106.06090v1 fatcat:zvkhinpcvzbmje4kjpwjs355qu

Multimodal Co-learning: Challenges, Applications with Datasets, Recent Advances and Future Directions [article]

Anil Rahate, Rahee Walambe, Sheela Ramanna, Ketan Kotecha
2021 arXiv   pre-print
To that end, in this work, we provide a comprehensive survey on the emerging area of multimodal co-learning that has not been explored in its entirety yet.  ...  However, in real-world tasks, typically, it is observed that one or more modalities are missing, noisy, lacking annotated data, have unreliable labels, and are scarce in training or testing and or both  ...  to influence the work reported in this paper.  ... 
arXiv:2107.13782v2 fatcat:s4spofwxjndb7leqbcqnwbifq4

Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Research [article]

Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, Rada Mihalcea
2020 arXiv   pre-print
We analyze the significant leaps responsible for its current relevance. Further, we attempt to chart a possible course for this field that covers many overlooked and unanswered questions.  ...  In this article, we discuss this perception by pointing out the shortcomings and under-explored, yet key aspects of this field that are necessary to attain true sentiment understanding.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of A*STAR.  ... 
arXiv:2005.00357v5 fatcat:gjzglyhtvvc3xnuaeqjocbp57u

Characterizing communities of hashtag usage on twitter during the 2020 COVID-19 pandemic by multi-view clustering

Iain J Cruickshank, Kathleen M Carley
2020 Applied Network Science  
In order to obtain high-quality clusters of the Twitter hashtags, we also propose a novel multi-view clustering technique that incorporates multiple different data types that can be used to describe how  ...  As such, analysis of social media data during the COVID-19 pandemic can produce unique insights into discussion topics and how those topics evolve over the course of the pandemic.  ...  Since many of the successful techniques from multi-view clustering require matrix or tensor factorizations, which can be computationally expensive (i.e.  ... 
doi:10.1007/s41109-020-00317-8 pmid:32953977 pmcid:PMC7492790 fatcat:dlo2qx6tcbhb3pyuo6ep7kw5cu

Associations between brain abnormalities and common genetic variants for schizophrenia: a narrative review of structural and functional neuroimaging findings

Zixuan Lin, Yicheng Long, Zhipeng Wu, Zhibiao Xiang, Yumeng Ju, Zhening Liu
2021 Annals of Palliative Medicine  
Multiple common genetic variants for schizophrenia including the ZNF804A, DTNBP1, DAOA, AKT1, NTRK3, and ERBB4 genes are reviewed.  ...  , and technological limitations; performing not only cross-sectional but also longitudinal observations; focusing on the effect of copy number variants; figuring out the complexity of epistasis and gene-environment  ...  Acknowledgments The authors would like to thank Ravi Sreyas for his help in language polishing work on this manuscript.  ... 
doi:10.21037/apm-21-1210 pmid:34412503 fatcat:zl3yc5vywrgw5fj46k5rit23mu
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