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Publications

Year Authors Title
  2012 Alfredo Maldonado-Guerra and Martin Emms First-order and second-order context representations: geometrical considerations and performance in word-sense disambiguation and discrimination Proceedings of the 11th International Conference on the Statistical Analysis of Textual Data (JADT 2012), pp676-686
  2011 Alfredo Maldonado-Guerra and Martin Emms Measuring the compositionality of collocations via word co-occurrence vectors: Shared task system description Proceedings of the Distributional Semantics and Compositionality workshop (DISCo 2011). , pp48-53
  2014 Arun Jayapal and Martin Emms and John Kelleher TCDSCSS: Dimensionality Reduction to Evaluate Texts of Varying Lengths - an IR Approach 8th International Workshop on Semantic Evaluation (SemEval 2014), pp619-623. DOI: http://dx.doi.org/10.3115/v1/s14-2109
  2009 Baoli Li, Martin Emms, Saturnino Luz, and Carl Vogel Exploring multilingual semantic role labeling Proceedings of the Thirteenth Conference on Computational Natural Language Learning (CoNLL 2009): Shared Task, pp73-78. DOI: http://dx.doi.org/10.3115/1596409.1596422
  2013 Martin Emms Dynamic EM in Neologism Evolution Intelligent Data Engineering and Automated Learning, pp286-293. DOI: http://dx.doi.org/10.1007/978-3-642-41278-3_35
  2012 Martin Emms On stochastic tree distances and their training via Expectation-Maximisation ICPRAM 2012 International Conference on Pattern Recognition Application and Methods, pp144-153. DOI: http://dx.doi.org/10.5220/0003864901440153
  2010 Martin Emms Trainable Tree Distance and application to Question Categorisation KONVENS 2010, pp123-127
  2008 Martin Emms Tree distance and some other variants of evalb LREC 2008
  2006 Martin Emms Variants of Tree Similarity in a Question Answering Task Linguistic Distances workshop held in conjunction with COLING 2006, pp100-108. DOI: http://dx.doi.org/10.3115/1641976.1641989
  2006 Martin Emms Clustering by Tree Distance for Parse Tree Normalisation NLUCS 2006, pp91-1000. DOI: http://dx.doi.org/10.5220/0002502400910100
  2005 Martin Emms Adapting Tree Distance to Answer Retrieval and Parser Evaluation International Workshop on Intelligent Linguistic Technologies
  2005 Martin Emms Tree Distance in Answer Retrieval and Parser Evaluation Natural Language Understanding and Cognitive Science. DOI: http://dx.doi.org/10.5220/0002565101550160
  2001 Martin Emms A Prolog Based Information Extraction System 14th International Conference on Applications of Prolog
  1996 Martin Emms Models for Polymorphic Lambek Calculus Logical Aspects of Computational Linguistics
  1995 Martin Emms Undecidability result for polymorphic lambek calculus Tenth Amsterdam Colloquium
  2013 Martin Emms and Alfredo Maldonado-Guerra Latent Ambiguity in Latent Semantic Analysis? ICPRAM 2013 (Int.Conf. on Pattern Recognition Applications and Methods), pp115-120. DOI: http://dx.doi.org/10.5220/0004178301150120
  2016 Martin Emms and Arun Jayapal Dynamic Generative model for Diachronic Sense Emergence Detection COLING, pp1362-1373
  2015 Martin Emms and Arun Jayapal An unsupervised EM method to infer time variation in sense probabilities ICON 2015 : 12th International Conference on Natural Language Processing, pp266-271
  2014 Martin Emms and Arun Jayapal Detecting change and emergence for multiword expressions EACL MWE Workshop, pp89-93. DOI: http://dx.doi.org/10.3115/v1/w14-0815
  1999 Martin Emms and Hans Leiss Extending the Type Checker of Standard ML by Polymorphic Recursion Theoretical Computer Science, 212
  2012 Martin Emms and Hector Franco-Penya On order equivalences between distance and similarity measures on sequences and trees ICPRAM 2012 International Conference on Pattern Recognition Application and Methods, pp15-24. DOI: http://dx.doi.org/10.5220/0003712500150024
  2012 Martin Emms and Hector-Hugo Franco-Penya Projecting Semantic Roles via Tai Mappings KONVENS 2012 Empirical Methods in Natural Languiage Processing, pp61-69
  2012 Martin Emms and Hector-Hugo Franco-Penya On the Expressivity of Alignment-Based Distance and Similarity Measures on Sequences and Trees in Inducing Orderings Mathematical Methodologies in Pattern Recognition and Machine Learning , pp1-18

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