Computational Linguistics and Intelligent Text Processing

1. Front Matter

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2. Lexical Resources

   1. Using Word Association Norms to Measure Corpus Representativeness

      • Reinhard Rapp

      Pages 1-13

   2. Optimality Theory as a Framework for Lexical Acquisition

      • Thierry Poibeau

      Pages 14-24

   3. Verb Clustering for Brazilian Portuguese

      • Carolina Scarton, Lin Sun, Karin Kipper-Schuler, Magali Sanches Duran, Martha Palmer, Anna Korhonen

      Pages 25-39

   4. Spreading Relation Annotations in a Lexical Semantic Network Applied to Radiology

      • Lionel Ramadier, Manel Zarrouk, Mathieu Lafourcade, Antoine Micheau

      Pages 40-51

   5. Issues in Encoding the Writing of Nepal’s Languages

      • Pat Hall, Bal Krishna Bal, Sagun Dhakhwa, Bhim Narayan Regmi

      Pages 52-67

   6. Compound Terms and Their Multi-word Variants: Case of German and Russian Languages

      • Elizaveta Clouet, Béatrice Daille

      Pages 68-78

   7. A Fully Automated Approach for Arabic Slang Lexicon Extraction from Microblogs

      • Hady ElSahar, Samhaa R. El-Beltagy

      Pages 79-91

   8. Simple TF·IDF Is Not the Best You Can Get for Regionalism Classification

      • Hiram Calvo

      Pages 92-101

   9. Improved Text Extraction from PDF Documents for Large-Scale Natural Language Processing

      • Jörg Tiedemann

      Pages 102-112

3. Document Representation

   1. Dependency-Based Semantic Parsing for Concept-Level Text Analysis

      • Soujanya Poria, Basant Agarwal, Alexander Gelbukh, Amir Hussain, Newton Howard

      Pages 113-127

   2. Obtaining Better Word Representations via Language Transfer

      • Changliang Li, Bo Xu, Gaowei Wu, Xiuying Wang, Wendong Ge, Yan Li

      Pages 128-137

   3. Exploring Applications of Representation Learning in Nepali

      • Anjan Nepal, Alexander Yates

      Pages 138-150

   4. Topic Models Incorporating Statistical Word Senses

      • Guoyu Tang, Yunqing Xia, Jun Sun, Min Zhang, Thomas Fang Zheng

      Pages 151-162

   5. How Preprocessing Affects Unsupervised Keyphrase Extraction

      • Rui Wang, Wei Liu, Chris McDonald

      Pages 163-176

4. Morphology, POS-tagging, and Named Entity Recognition

   1. Methods and Algorithms for Unsupervised Learning of Morphology

      • Burcu Can, Suresh Manandhar

      Pages 177-205

   2. Morphological Analysis of the Bishnupriya Manipuri Language Using Finite State Transducers

      • Nayan Jyoti Kalita, Navanath Saharia, Smriti Kumar Sinha

      Pages 206-213

   3. A Hybrid Approach to the Development of Part-of-Speech Tagger for Kafi-noonoo Text

      • Zelalem Mekuria, Yaregal Assabie

      Pages 214-224

   4. Modified Differential Evolution for Biochemical Name Recognizer

      • Utpal Kumar Sikdar, Asif Ekbal, Sriparna Saha

      Pages 225-236

5. Syntax and Parsing

   1. Extended CFG Formalism for Grammar Checker and Parser Development

      • Daiga Deksne, Inguna Skadiņa, Raivis Skadiņš

      Pages 237-249

This two-volume set, consisting of LNCS 8403 and LNCS 8404, constitutes the thoroughly refereed proceedings of the 14th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2014, held in Kathmandu, Nepal, in April 2014. The 85 revised papers presented together with 4 invited papers were carefully reviewed and selected from 300 submissions. The papers are organized in the following topical sections: lexical resources; document representation; morphology, POS-tagging, and named entity recognition; syntax and parsing; anaphora resolution; recognizing textual entailment; semantics and discourse; natural language generation; sentiment analysis and emotion recognition; opinion mining and social networks; machine translation and multilingualism; information retrieval; text classification and clustering; text summarization; plagiarism detection; style and spelling checking; speech processing; and applications.

• clustering and classification
• document management and text processing
• information retrieval
• information systems applications
• lexical semantics
• machine learning
• natural language processing
• semantic networks
• topic modeling
• unsupervised learning

• Center for Computing Research, National Polytechnic Institute, Mexico D.F., Mexico

  Alexander Gelbukh

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