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[PDF] Top 20 An active learning-enabled annotation system for clinical named entity recognition

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An active learning-enabled annotation system for clinical named entity recognition

An active learning-enabled annotation system for clinical named entity recognition

... This finding could be due to multiple reasons. First, although AL selected more informative sentences and required fewer sentences for building NER models, it often selects longer sentences with more entities, which take ... See full document

10

Practical, Efficient, and Customizable Active Learning for Named Entity Recognition in the Digital Humanities

Practical, Efficient, and Customizable Active Learning for Named Entity Recognition in the Digital Humanities

... The best known NER systems among humanists are Stanford NER (Finkel et al., 2005), with pre- trained models in several languages and an in- terface for building new models, and among re- searchers interested in NER for ... See full document

12

Proactive Learning for Named Entity Recognition

Proactive Learning for Named Entity Recognition

... proactive learning has been proposed to model dif- ferent types of experts (Donmez and Carbonell, 2008, ...Proactive learning assumes that (1) not all annotators are perfect, but that there is at least one ... See full document

9

Active learning for ontological event extraction incorporating named entity recognition and unknown word handling

Active learning for ontological event extraction incorporating named entity recognition and unknown word handling

... Active learning is the research topic of choosing ‘infor- mative’ documents for manual annotation such that the would-be annotations on the documents may promote the training of supervised ... See full document

18

Annotating named entities in clinical text by combining pre annotation and active learning

Annotating named entities in clinical text by combining pre annotation and active learning

... of clinical text, an- notated for named entities, a method that combines pre-tagging with a version of ac- tive learning is ...cilitate annotation and to avoid bias, two alternative automatic ... See full document

7

Named Entity Recognition Using Machine Learning Approaches

Named Entity Recognition Using Machine Learning Approaches

... a Named Entity Recognition based on maximum entropy system for extracting entities present in the biomedical text and reviews its ...data annotation is ... See full document

11

Contributions to Clinical Named Entity Recognition in Portuguese

Contributions to Clinical Named Entity Recognition in Portuguese

... machine learning models that identify and classify named entities (NEs), the lat- ter have to be annotated on a collection of texts, which can be used as training and/or testing ...1,104 clinical ... See full document

11

On Proper Unit Selection in Active Learning: Co Selection Effects for Named Entity Recognition

On Proper Unit Selection in Active Learning: Co Selection Effects for Named Entity Recognition

... of annotation effort according to some cost mea- ...real annotation setting, however, it is unnatural, and therefore hard for humans to annotate single, possibly isolated tokens, leading to bad ... See full document

9

Deep Active Learning for Named Entity Recognition

Deep Active Learning for Named Entity Recognition

... scale. Active learn- ing seeks to ameliorate this problem by strategi- cally choosing which examples to annotate, in the hope of getting greater performance with fewer ...The learning process consists of ... See full document

5

Stopping Criteria for Active Learning of Named Entity Recognition

Stopping Criteria for Active Learning of Named Entity Recognition

... classification system may want to set a minimum absolute performance for the system to be ...stop active learning if estimated performance reaches the threshold set by the ... See full document

8

An attention-based deep learning model for clinical named entity recognition of Chinese electronic medical records

An attention-based deep learning model for clinical named entity recognition of Chinese electronic medical records

... of recognition performance shown in Table 8, all three models can recognize the entity when the keyword is closed to it in the context, but CRF model can’t capture context infor- mation of a little bit ... See full document

11

Bundschus, Markus
  

(2010):


	From Text to Knowledge: Bridging the Gap with Probabilistic Graphical Models.


Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik

Bundschus, Markus (2010): From Text to Knowledge: Bridging the Gap with Probabilistic Graphical Models. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik

... The performance of the cascaded CRF on the data set provided by [163] is on par with the multilayer NN and superior to the best GM. This may be due to the discriminative nature of CRFs and NNs, which could be an ... See full document

170

Exploiting Morphology in Turkish Named Entity Recognition System

Exploiting Morphology in Turkish Named Entity Recognition System

... In this paper, we explored the effects of using fea- tures like root, POS tag, proper noun and case to the performance of NER task. All these features seem to improve the system significantly. We also explored a ... See full document

6

Named Entity Recognition System for Dialectal Arabic

Named Entity Recognition System for Dialectal Arabic

... bic Named Entity Recognition (NER) ad- dresses the task for Modern Standard Ara- bic (MSA) and mainly focuses on the newswire ...NER system for DA specif- ically focusing on the Egyptian ... See full document

9

Named Entity Recognition System for Punjabi Language Text

Named Entity Recognition System for Punjabi Language Text

... “Named Entity”, the word “Named” means to any name which can be belong to the person, place, location, dates , city, state, country ...the named entity from a ...a named ... See full document

5

Multi Task Active Learning for Linguistic Annotations

Multi Task Active Learning for Linguistic Annotations

... Supervised machine learning methods have success- fully been applied to many NLP tasks in the last few decades. These techniques have demonstrated their superiority over both hand-crafted rules and unsu- pervised ... See full document

9

A Joint Chinese Named Entity Recognition and Disambiguation System

A Joint Chinese Named Entity Recognition and Disambiguation System

... the named entities has been established as an important task in several areas, including topic detection and tracking, machine translation, and information retrieval (Cucerzan, ...fore, named entity ... See full document

6

Building a Named Entity Recognizer in Three Days: Application to Disease Name Recognition in Bulgarian Epicrises

Building a Named Entity Recognizer in Three Days: Application to Disease Name Recognition in Bulgarian Epicrises

... Bulgarian clinical epicrises, where both the language and the domain are different from those in mainstream research, which has focused on PubMed arti- cles in ...manual annotation: we achieve ...goal: ... See full document

8

Named Entity Recognition for Novel Types by Transfer Learning

Named Entity Recognition for Novel Types by Transfer Learning

... fine-grained entity typol- ogy has been shown to improve other tasks such as re- lation extraction (Ling and Weld, 2012) and question answering (Lee et ...Transfer Learning for ... See full document

7

TLR at BSNLP2019: A Multilingual Named Entity Recognition System

TLR at BSNLP2019: A Multilingual Named Entity Recognition System

... multilingual named en- tity recognition (NER) proposes to participants to test their system under a multilingual ...sole recognition of enti- ties while other steps will be covered in our ... See full document

6

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