ACL RD-TEC 1.0 Summarization of W02-0301

Paper Title:
TUNING SUPPORT VECTOR MACHINES FOR BIOMEDICAL NAMED ENTITY RECOGNITION

Authors: Jun'ichi Kazama and Takaki Makino and Yoshihiro Ohta and Jun'ichi Tsujii

Other assigned terms:

  • annotated corpora
  • annotated corpus
  • annotation
  • approach
  • association for computational linguistics
  • biomedical domain
  • biomedical information
  • cache
  • case
  • character type
  • class distribution
  • corpora
  • data sparseness
  • data sparseness problem
  • determiners
  • disjunction
  • distribution
  • entity class
  • entity recognition task
  • entropy
  • experimental results
  • f-score
  • feature
  • feature description
  • feature set
  • feature sets
  • feature space
  • genia
  • genia corpus
  • hmm state feature
  • identification task
  • implementation
  • interpretation
  • kernel evaluation
  • kernel function
  • knowledge
  • large corpus
  • linguistic
  • linguistics
  • mapping
  • measures
  • medline
  • method
  • n-gram
  • named entities
  • named entity
  • named entity task
  • natural language
  • ne task
  • nlp tasks
  • noise
  • noun phrases
  • nouns
  • optimization problem
  • parallelism
  • part-of-speech
  • part-of-speech information
  • part-of-speech tag
  • part-of-speech tags
  • penn treebank
  • phrase
  • pos information
  • precision
  • probability
  • process
  • query
  • recognition accuracy
  • recognition task
  • representations
  • research topic
  • semantic
  • semantic class
  • sentence
  • sentences
  • sparseness problem
  • state feature
  • statistics
  • substring
  • support vector
  • svms
  • tag set
  • tagging model
  • tags
  • technique
  • text
  • training
  • training data
  • training samples
  • training time
  • treebank
  • unbalanced class distribution
  • vocabulary
  • word
  • word features
  • words

Extracted Section Types:


This page last edited on 10 May 2017.

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