Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data

12th China National Conference, CCL 2013 and First International Symposium, NLP-NABD 2013, Suzhou, China, October 10-12, 2013. Proceedings

Editors:

ISBN: 978-3-642-41490-9 (Print) 978-3-642-41491-6 (Online)

Table of contents (32 chapters)

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  1. Front Matter

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  2. Word Segmentation

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      Pages 1-12

      Improving Chinese Word Segmentation Using Partially Annotated Sentences

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      Pages 13-24

      Chinese Natural Chunk Research Based on Natural Annotations in Massive Scale Corpora

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      Pages 25-35

      A Kalman Filter Based Human-Computer Interactive Word Segmentation System for Ancient Chinese Texts

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      Pages 36-43

      Chinese Word Segmentation with Character Abstraction

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      Pages 44-51

      A Refined HDP-Based Model for Unsupervised Chinese Word Segmentation

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      Pages 52-60

      Enhancing Chinese Word Segmentation with Character Clustering

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      Pages 61-72

      Integrating Multi-source Bilingual Information for Chinese Word Segmentation in Statistical Machine Translation

  3. Open-Domain Q&A

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      Pages 73-84

      Interactive Question Answering Based on FAQ

  4. Discourse, Coreference and Pragmatics

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      Pages 85-96

      Document Oriented Gap Filling of Definite Null Instantiation in FrameNet

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      Pages 97-108

      Interesting Linguistic Features in Coreference Annotation of an Inflectional Language

  5. Statistical and Machine Learning Methods in NLP

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      Pages 109-119

      Semi-supervised Learning with Transfer Learning

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      Pages 120-130

      Online Distributed Passive-Aggressive Algorithm for Structured Learning

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      Pages 131-143

      Power Law for Text Categorization

  6. Semantics

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      Pages 144-153

      Natural Language Understanding for Grading Essay Questions in Persian Language

  7. Text Mining, Open-Domain Information Extraction and Machine Reading of the Web

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      Pages 154-165

      Learning to Extract Attribute Values from a Search Engine with Few Examples

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      Pages 166-178

      User-Characteristics Topic Model

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      Pages 179-189

      Mining User Preferences for Recommendation: A Competition Perspective

  8. Sentiment Analysis, Opinion Mining and Text Classification

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      Pages 190-202

      A Classification-Based Approach for Implicit Feature Identification

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      Pages 203-213

      Role of Emoticons in Sentence-Level Sentiment Classification

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      Pages 214-226

      Emotional McGurk Effect? A Cross-Cultural Investigation on Emotion Expression under Vocal and Facial Conflict

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