natural language processing tasks
Robust to Noise Models in Natural Language Processing Tasks
... There are a lot of noisy texts surrounding a person in modern life. A traditional approach is to use spelling correction, yet the existing solutions are far from perfect. We propose a robust to noise word embeddings ...
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Evaluating unsupervised learning for natural language processing tasks
... The development of unsupervised learning methods for natural language processing tasks has become an important and popular area of research. The primary advantage of these methods is that they ...
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Quantifying Uncertainties in Natural Language Processing Tasks
... for natural language processing (NLP) ...and language modeling using convolutional and recurrent neural network models, we show that explicitly modeling uncertainties is not only necessary to ...
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Fast and Accurate Decision Trees for Natural Language Processing Tasks
... Before describing our proposed optimizations, we have to clarify our view of the algorithm’s data representation style. The standard way to view a dataset is that of a examples (instances) having a number of attributes ...
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Evaluation of Machine Learning Methods for Natural Language Processing Tasks
... in language technology. Most natural language processing (NLP) problems can be for- mulated as classification problems (given some object and its context, decide on the class of this ...
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Learning Representations for Weakly Supervised Natural Language Processing Tasks
... A growing body of theoretical and empirical evidence suggests that traditional, manually crafted features for a variety of NLP tasks limit systems’ performance in this weakly supervised learning for two reasons. ...
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Convolution Kernels with Feature Selection for Natural Language Processing Tasks
... Since natural language data take the form of sequences of words, and are generally ana- lyzed using discrete structures, such as trees (parsed trees) and graphs (relational graphs), discrete ker- nels, such ...
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MAE and MAI: Lightweight Annotation and Adjudication Tools
... for natural language processing tasks has been steadily increasing over the years: text processing challenges such as those associated with the SemEval workshops (Erk and Strapparava, ...
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Text Mining in Archaeology : Extracting Information from Archaeological Reports
... the Natural Language Processing (NLP) tasks of Named Entity Recognition, Relation Extraction, Negation Detection and Word-Sense disambiguation using hand- crafted rules and terminological ...
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Analysis of Statistical Parsing in Natural Language Processing
... Evaluation is important in all NLP tasks. It has always been a problem in disambiguation research, as the only way to judge the performance of a disambiguator is to manually check its output. Manual checking is ...
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Similarity Based Alignment of Monolingual Corpora for Text Simplification Purposes
... annotation tasks, Snow et ...of natural language processing has used crowdsourcing for various tasks within the NLP area, often by the use of Amazon’s Mechanical Turk (Callison-burch et ...
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Text mining in archaeology: Extracting information from archaeological reports
... the Natural Language Processing (NLP) tasks of Named Entity Recognition, Relation Extraction, Negation Detection and Word Sense disambiguation using hand-crafted rules and terminological ...
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Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
... Before closing this brief welcome, we would like to thank the entire organizing committee for their long efforts to create and event that we hope will be memorable for you. Program chairs Greg Kondrak and Taro Watanabe ...
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Investigation of annotator’s behaviour using eye tracking data
... for natural language processing (NLP) ...NLP tasks, in par- ticular semantic and discourse processing that require deeper language understand- ...
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Clairlib: A Toolkit for Natural Language Processing, Information Retrieval, and Network Analysis
... In this paper we present Clairlib, an open- source toolkit for Natural Language Process- ing, Information Retrieval, and Network Anal- ysis. Clairlib provides an integrated frame- work intended to simplify ...
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Can Natural Language Processing Become Natural Language Coaching?
... for tasks like these, the challenge is to go beyond rec- ognizing and correcting the errors to helping the writer understand why the choices they are making are not ...
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Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
... Before closing this brief welcome, we would like to thank the entire organizing committee for their long efforts to create and event that we hope will be memorable for you. Program chairs Greg Kondrak and Taro Watanabe ...
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Recurrent Memory Networks for Language Modeling
... many natural lan- guage processing (NLP) ...on language modeling and sentence comple- tion tasks. On language modeling, RMN out- performs Long Short-Term Memory (LSTM) network on three ...
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Comparison of Diverse Decoding Methods from Conditional Language Models
... neural language models, which train a neural net to map from one sequence to an- other, have had enormous success in natural lan- guage processing tasks such as machine transla- tion ...
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Proceedings of the IJCNLP 2017, Shared Tasks
... on Natural Language Processing (IJCNLP 2017) took place in Taipei, Taiwan from November 27 to December 1, ...Chinese Language Processing (ACLCLP), and it was hosted by the Asian ...
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