CoNLL 2014 - 18th Conference on Computational Natural Language Learning (CoNLL-2014)

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, dialogue, 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