Computational Linguistics and Intelligent Text Processing

General Techniques.- Unsupervised Feature Adaptation for Cross-Domain NLP with an Application to Compositionality Grading.- Syntactic Dependency-Based N-grams: More Evidence of Usefulness in Classification.- Lexical Resources.- A Quick Tour of BabelNet 1.1 (Invited paper).- Automatic Pipeline Construction for Real-Time Annotation.- A Multilingual GRUG Treebank for Underresourced Languages.- Creating an Annotated Corpus for Extracting Canonical Citations from Classics-Related Texts by Using Active Annotation.- Approaches of Anonymisation of an SMS Corpus.- A Corpus Based Approach for the Automatic Creation of Arabic Broken Plural Dictionaries.- Temporal Classifiers for Predicting the Expansion of Medical Subject Headings.- Knowledge Discovery on Incompatibility of Medical Concepts.- Extraction of Part-Whole Relations from Turkish Corpora.- Chinese Terminology Extraction Using EM-Based Transfer Learning Method.- Orthographic Transcription for Spoken Tunisian Arabic.- Morphology and Tokenization.- An Improved Stemming Approach Using HMM for a Highly Inflectional Language.- Semi-automatic Acquisition of Two-Level Morphological Rules for Iban Language.- Finite State Morphology for Amazigh Language.- New Perspectives in Sinographic Language Processing through the Use of Character Structure.- The Application of Kalman Filter Based Human-Computer Learning Model to Chinese Word Segmentation.- Machine Learning for High-Quality Tokenization Replicating Variable Tokenization Schemes.- Syntax and Named Entity Recognition Structural Prediction in Incremental Dependency Parsing.- Semi-supervised Constituent Grammar Induction Based on Text
Chunking Information.- Turkish Constituent Chunking with Morphological and Contextual Features.- Enhancing Czech Parsing with Verb Valency Frames.- An Automatic Approach to Treebank Error Detection Using a
Dependency Parser.- Topic-Oriented Words as Features for Named Entity Recognition (Best Paper Award, Second Place).- Named Entities in