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Conference on Empirical Methods in Natural Language Processing

EMNLP 2009

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Important: EMNLP 2009 is running a double-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, double-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.

Finite-state Methods
Part-of-speech Tagging
Word Segmentation
Grammar Induction/Development
Parsing Algorithms and Implementations
Mathematical Linguistics
Grammatical Formalisms
Lexical Semantics
Ontological Semantics
Formal Semantics and Logic
Word Sense Disambiguation
Semantic Role Labeling
Textual Entailment and Paraphrasing
Semantic Knowledge Induction
Coreference Resolution
Anaphora Resolution
Language Generation
Statistical and Machine Learning Methods
Formalisms and Metrics of Statistical and Machine Learning Methods
Language Modeling for Text Processing
Bilingual Alignment
Parallel Text
Machine Translation
Information Retrieval
Question Answering
Cross-language Information Retrieval
Term Extraction
Cross-language Information Extraction
Named Entity Recognition
Relation/Event Extraction
Entity Disambiguation
Temporal/Spatial Information Extraction
Information Extraction
Text Mining
Sentiment Analysis
Subjectivity Analysis
Opinion Mining and Extraction
Evidentiality and Hedging
Text Classification
Speech Recognition and Synthesis
Spoken Language Understanding and Generation
Language Modeling for Spoken Language
Multimodal Representations and Processing
Rich Transcription and Spoken Information Retrieval
Speech Translation
NLP Applications
NLP with Vertical Domains Including Biomedical and Legal Text
Educational Applications
Ontology Development
Lexicon Development
Treebank and Corpus Development
Evaluation Metrics
User Studies
Annotation Methods
Bilingual Lexicons
Multilingual Resources
NLP on Noisy Unstructured Text Including Emails, Blogs and SMS
NLP on Wikipedia and Other Collaboratively Constructed Resources

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