Topics
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We solicit papers on all areas that may be of interest to the SIGDAT and
SIGNLL communities, including but not limited to:
* Phonology and morphology, tagging and chunking, segmentation
* Syntax and parsing
* Semantics
* Discourse, dialog, and pragmatics
* Summarization and generation
* Machine translation
* Information retrieval and question answering
* Information extraction
* Spoken language processing
* Text mining and natural language processing applications
* Multilinguality
* Sentiment analysis and opinion mining
* Models of language in social context
* NLP for the Web
* Computational models of human language acquisition
* Supervised, unsupervised and semi-supervised machine learning
methods applied to natural language, including speech
* Statistical methods (Bayesian learning, graphical models, kernel
methods, statistical models for structured problems)
* Symbolic learning methods (rule induction and decision tree
learning, lazy learning, inductive logic programming, analytical
learning, transformation-based error-driven learning)
* Biologically-inspired methods (Neural Networks, Evolutionary Computing)
* Reinforcement learning, active learning
* Learning architectures for structural and relational NLP tasks
* Computational models of language evolution and historical change
* Computational learning theory analysis of language learning
* Empirical and theoretical comparisons of language learning
methods, including novel evaluation methods
* Models of induction and analogy in linguistics