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Improving Dependency Parsing Using Word Clusters

2015-10-22
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Release : 2015-10-22
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Kind : eBook
Book Rating : 551/5 ( reviews)

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Book Synopsis Improving Dependency Parsing Using Word Clusters by : Jostein Lien

Download or read book Improving Dependency Parsing Using Word Clusters written by Jostein Lien. This book was released on 2015-10-22. Available in PDF, EPUB and Kindle. Book excerpt: Several studies have attempted to improve the accuracy in dependency parsing by including information about word clusters into the parsing models. The use of word clusters are typically motivated by the shortage of labeled training data and domain adaption, attempting to influence a parsing model for use on data from a new domain. This book shows the effect of using cluster-based features in MaltParser, a data-driven parser for inductive dependency parsing. Different clustering features are used for generating clusters, using the K-means clustering algorithm. The clusters are used as a source of additional information in an expanded feature model used by the MaltParser system. Parsing experiments are performed on several different data sets, including the Wall Street Journal and texts from various web domains. Significantly improved parsing results are reported when using a cluster-informed parser compared to the baseline parser. The contents of this book might be of interest to anyone interested in the application of machine learning in language technology.

Semi-Supervised Dependency Parsing

2015-07-16 Language Arts & Disciplines
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Release : 2015-07-16
Genre : Language Arts & Disciplines
Kind : eBook
Book Rating : 522/5 ( reviews)

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Book Synopsis Semi-Supervised Dependency Parsing by : Wenliang Chen

Download or read book Semi-Supervised Dependency Parsing written by Wenliang Chen. This book was released on 2015-07-16. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Having become increasingly popular in recent years, one of the main reasons for their success is that they can make use of large unlabeled data together with relatively small labeled data and have shown their advantages in the context of dependency parsing for many languages. Various semi-supervised dependency parsing approaches have been proposed in recent works which utilize different types of information gleaned from unlabeled data. The book offers readers a comprehensive introduction to these approaches, making it ideally suited as a textbook for advanced undergraduate and graduate students and researchers in the fields of syntactic parsing and natural language processing.

Ensembles of Diverse Clustering-based Discriminative Dependency Parsers

2012 Cluster analysis
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Release : 2012
Genre : Cluster analysis
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Book Synopsis Ensembles of Diverse Clustering-based Discriminative Dependency Parsers by : Marzieh Razavi

Download or read book Ensembles of Diverse Clustering-based Discriminative Dependency Parsers written by Marzieh Razavi. This book was released on 2012. Available in PDF, EPUB and Kindle. Book excerpt: Syntactic parsing and dependency parsing in particular are a core component of many Natural Language Processing (NLP) tasks and applications. Improvements in dependency parsing can help improve machine translation and information extraction applications among many others. In this thesis, we extend the framework of (Koo, Carreras, and Collins, 2008) for dependency parsing which uses a single clustering method for semi-supervised learning. We make use of multiple diverse clustering methods to build multiple discriminative dependency parsing models in the Maximum Spanning Tree (MST) parsing framework (McDonald, Crammer, and Pereira, 2005). All of these diverse clustering-based parsers are then combined together using a novel ensemble model, which performs exact inference on the shared hypothesis space of all the parser models. We show that diverse clustering-based parser models and the ensemble method together significantly improves unlabeled dependency accuracy from 90.82% to 92.46% on Section 23 of the Penn Treebank. We also show significant improvements in domain adaptation to the Switchboard and Brown corpora.

Neural Information Processing

2016-09-30 Computers
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Release : 2016-09-30
Genre : Computers
Kind : eBook
Book Rating : 879/5 ( reviews)

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Book Synopsis Neural Information Processing by : Akira Hirose

Download or read book Neural Information Processing written by Akira Hirose. This book was released on 2016-09-30. Available in PDF, EPUB and Kindle. Book excerpt: The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitutes the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.

Natural Language Understanding and Intelligent Applications

2016-11-30 Computers
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Release : 2016-11-30
Genre : Computers
Kind : eBook
Book Rating : 967/5 ( reviews)

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Book Synopsis Natural Language Understanding and Intelligent Applications by : Chin-Yew Lin

Download or read book Natural Language Understanding and Intelligent Applications written by Chin-Yew Lin. This book was released on 2016-11-30. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the joint refereed proceedings of the 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and the 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, held in Kunming, China, in December 2016. The 48 revised full papers presented together with 41 short papers were carefully reviewed and selected from 216 submissions. The papers cover fundamental research in language computing, multi-lingual access, web mining/text mining, machine learning for NLP, knowledge graph, NLP for social network, as well as applications in language computing.

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