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You're reading from  Natural Language Processing and Computational Linguistics

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Published inJun 2018
Reading LevelBeginner
PublisherPackt
ISBN-139781788838535
Edition1st Edition
Languages
Python
Tools
Spacy
Concepts
Mobile Application Development
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Bhargav Srinivasa-Desikan
Bhargav Srinivasa-Desikan
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Bhargav Srinivasa-Desikan

Bhargav Srinivasa-Desikan is a research engineer working for INRIA in Lille, France. He is a part of the MODAL (Models of Data Analysis and Learning) team, and he works on metric learning, predictor aggregation, and data visualization. He is a regular contributor to the Python open source community, and completed Google Summer of Code in 2016 with Gensim where he implemented Dynamic Topic Models. He is a regular speaker at PyCons and PyDatas across Europe and Asia, and conducts tutorials on text analysis using Python.
Read more about Bhargav Srinivasa-Desikan

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References

[1] A survey of named entity recognition and classification:
https://nlp.cs.nyu.edu/sekine/papers/li07.pdf

[2] Annotation Subtypes:
https://catalog.ldc.upenn.edu/docs/LDC2005T33/BBN-Types-Subtypes.html

[3] Named Entity Recognition and Resolution for Literary Studies:
https://pure.uva.nl/ws/files/2676433/168352_2014_VanDalenOskam_07_Namescape.pdf

[4] Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data:
https://repository.upenn.edu/cgi/viewcontent.cgi?referer=&httpsredir=1&article=1162&context=cis_papers

[5] Natural Language Processing: Semantic Aspects:
https://books.google.fr/books?id=YXv6AQAAQBAJ&source=gbs_navlinks_s

[6] Stanford NER:
https://nlp.stanford.edu/software/CRF-NER.shtml

[7] Testing NLTK and Stanford NER Taggers for Accuracy:
https://pythonprogramming.net/testing-stanford-ner-taggers-for-accuracy...

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Natural Language Processing and Computational Linguistics
Published in: Jun 2018Publisher: PacktISBN-13: 9781788838535
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Bhargav Srinivasa-Desikan

Bhargav Srinivasa-Desikan is a research engineer working for INRIA in Lille, France. He is a part of the MODAL (Models of Data Analysis and Learning) team, and he works on metric learning, predictor aggregation, and data visualization. He is a regular contributor to the Python open source community, and completed Google Summer of Code in 2016 with Gensim where he implemented Dynamic Topic Models. He is a regular speaker at PyCons and PyDatas across Europe and Asia, and conducts tutorials on text analysis using Python.
Read more about Bhargav Srinivasa-Desikan

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