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Link to original content: http://link.springer.com/book/10.1007/978-3-319-77113-7
Computational Linguistics and Intelligent Text Processing: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part I | SpringerLink
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Computational Linguistics and Intelligent Text Processing

18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part I

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Alexander Gelbukh

    1. CIC, Instituto Politécnico Nacional, Mexico City, Mexico

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10761)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: CICLing 2017.

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About this book

The two-volume set LNCS 10761 + 10762 constitutes revised selected papers from the CICLing 2017 conference which took place in Budapest, Hungary, in April 2017.

The total of 90 papers presented in the two volumes was carefully reviewed and selected from numerous submissions. In addition, the proceedings contain 4 invited papers.

The papers are organized in the following topical sections:

Part I: general; morphology and text segmentation; syntax and parsing; word sense disambiguation; reference and coreference resolution; named entity recognition; semantics and text similarity; information extraction; speech recognition; applications to linguistics and the humanities.

Part II: sentiment analysis; opinion mining; author profiling and authorship attribution; social network analysis; machine translation; text summarization; information retrieval and text classification; practical applications. 

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Table of contents (45 papers)

  1. Front Matter

    Pages I-XIX
    Download chapter PDF

  2. General

    1. Front Matter

      Pages 1-1
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    2. Overview of Character-Based Models for Natural Language Processing

      • Heike Adel, Ehsaneddin Asgari, Hinrich Schütze
      Pages 3-16

    3. Pooling Word Vector Representations Across Models

      • Rajendra Banjade, Nabin Maharjan, Dipesh Gautam, Frank Adrasik, Arthur C. Graesser, Vasile Rus
      Pages 17-29

    4. Strategies to Select Examples for Active Learning with Conditional Random Fields

      • Vincent Claveau, Ewa Kijak
      Pages 30-43

    5. Label-Dependencies Aware Recurrent Neural Networks

      • Yoann Dupont, Marco Dinarelli, Isabelle Tellier
      Pages 44-66

    6. Universal Computational Formalisms and Developer Environment for Rule-Based NLP

      • Svetlana Sheremetyeva
      Pages 67-78

  3. Morphology and Text Segmentation

    1. Front Matter

      Pages 79-79
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    2. Several Ways to Use the Lingwarium.org Online MT Collaborative Platform to Develop Rich Morphological Analyzers

      • Vincent Berment, Christian Boitet, Jean-Philippe Guilbaud, Jurgita Kapočiūtė-Dzikienė
      Pages 81-86

    3. A Trie-structured Bayesian Model for Unsupervised Morphological Segmentation

      • Murathan Kurfalı, Ahmet Üstün, Burcu Can
      Pages 87-98

    4. Building Morphological Chains for Agglutinative Languages

      • Serkan Ozen, Burcu Can
      Pages 99-109

    5. Joint PoS Tagging and Stemming for Agglutinative Languages

      • Necva Bölücü, Burcu Can
      Pages 110-122

    6. Hungarian Particle Verbs in a Corpus-Driven Approach

      • Ágnes Kalivoda
      Pages 123-133

    7. HANS: A Service-Oriented Framework for Chinese Language Processing

      • Lung-Hao Lee, Kuei-Ching Lee, Yuen-Hsien Tseng
      Pages 134-142

  4. Syntax and Parsing

    1. Front Matter

      Pages 143-143
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    2. Learning to Rank for Coordination Detection

      • Xun Wang, Rumeng Li, Hiroyuki Shindo, Katsuhito Sudoh, Masaaki Nagata
      Pages 145-157

    3. Classifier Ensemble Approach to Dependency Parsing

      • Silpa Kanneganti, Vandan Mujadia, Dipti M. Sharma
      Pages 158-169

    4. Evaluation and Enrichment of Stanford Parser Using an Arabic Property Grammar

      • Raja Bensalem Bahloul, Nesrine Kadri, Kais Haddar, Philippe Blache
      Pages 170-182

  5. Word Sense Disambiguation

    1. Front Matter

      Pages 183-183
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    2. SenseDependency-Rank: A Word Sense Disambiguation Method Based on Random Walks and Dependency Trees

      • Marco Antonio Sobrevilla-Cabezudo, Arturo Oncevay-Marcos, Andrés Melgar
      Pages 185-194
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Other volumes

  1. Computational Linguistics and Intelligent Text Processing

  2. Computational Linguistics and Intelligent Text Processing

Editors and Affiliations

  • CIC, Instituto Politécnico Nacional, Mexico City, Mexico

    Alexander Gelbukh

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