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2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning


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Important: EMNLP-CoNLL 2007 is running a blind review process. In preparing your manuscript, do not include any information which could reveal your identity, or that of your co-authors. The title section of your manuscript should not contain any author names, email addresses, or affiliation status. If you do include any author names on the title page, your submission will be automatically rejected. In the body of your submission, you should eliminate all direct references to your own previous work. That is, avoid phrases such as "this contribution generalizes our results for XYZ". Also, please do not disproportionately cite your own previous work. In other words, make your submission as anonymous as possible. We need your cooperation in our effort to maintain a fair, blind reviewing process - and to consider all submissions equally.

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Please use the list of topics below to characterize your submission. Check all categories that seem appropriate.

automaton induction
bilingual alignment
computational semantics
coreference resolution
data mining
dimensionality reduction
educational applications
finite-state methods
grammar formalisms
grammar learning (empirical)
grammar learning (theoretical)
information extraction
information navigation
information retrieval
knowledge discovery
language modeling
large document collections
learning theory
lexical acquisition
lexical semantics
linguistic resources
low-density languages
machine learning
machine translation
modeling techniques
multimodal communication
named-entity recognition
opinion extraction
PAC learning
parallel text
part-of-speech tagging
question answering
relation extraction
scalable algorithms
semantic roles
sentiment analysis
speech recognition
speech synthesis
syntactic chunking
syntax induction
term extraction
text categorization
text segmentation
textual entailment
topic discovery
user applications
word boundaries
word senses

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