论文信息 - Natural language processing and the Now-or-Never bottleneck

Natural language processing and the Now-or-Never bottleneck

Abstract Researchers, motivated by the need to improve the efficiency of natural language processing tools to handle web-scale data, have recently arrived at models that remarkably match the expected features of human language processing under the Now-or-Never bottleneck framework. This provides additional support for said framework and highlights the research potential in the interaction between applied computational linguistics and cognitive science.

Carlos Gómez-Rodríguez | Carlos Gómez-Rodríguez

[1] Joakim Nivre,et al. A Transition-Based System for Joint Part-of-Speech Tagging and Labeled Non-Projective Dependency Parsing , 2012, EMNLP.

[2] Noah A. Smith,et al. Transition-Based Dependency Parsing with Stack Long Short-Term Memory , 2015, ACL.

[3] Joakim Nivre,et al. An Efficient Algorithm for Projective Dependency Parsing , 2003, IWPT.

[4] Stephen Clark,et al. Syntactic Processing Using the Generalized Perceptron and Beam Search , 2011, CL.

[5] Danqi Chen,et al. A Fast and Accurate Dependency Parser using Neural Networks , 2014, EMNLP.

[6] Joakim Nivre,et al. Divisible Transition Systems and Multiplanar Dependency Parsing , 2013, CL.

[7] Andrew McCallum,et al. Transition-based Dependency Parsing with Selectional Branching , 2013, ACL.

[8] Joakim Nivre,et al. Algorithms for Deterministic Incremental Dependency Parsing , 2008, CL.

[9] Joakim Nivre,et al. MaltParser: A Language-Independent System for Data-Driven Dependency Parsing , 2007, Natural Language Engineering.

[10] Jun'ichi Tsujii,et al. Incremental Joint Approach to Word Segmentation, POS Tagging, and Dependency Parsing in Chinese , 2012, ACL.

[11] Giorgio Satta,et al. A Polynomial-Time Dynamic Oracle for Non-Projective Dependency Parsing , 2014, EMNLP.

[12] Joakim Nivre,et al. Incrementality in Deterministic Dependency Parsing , 2004 .