Titlebook: Natural Language Processingand Information Systems; 16th International C Rafael Mu?oz,Andrés Montoyo,Elisabeth Métais Conference proceeding

accrete

Extracting Explicit and Implicit Causal Relations from Sparse, Domain-Specific Textsth causal verbs, e.g. “to cause”. However, the challenges of extracting causal relations from domain-specific texts have been overlooked. Domain-specific texts are rife with causal relations that are implicitly expressed using verbal and non-verbal patterns, e.g. “reduce”, “drop in”, “due to”. Also,

Virtues

Frenetic

Improving Subtree-Based Question Classification Classifiers with Word-Cluster Modelsas been indicated that [10] it is helpful for question classification problem. The authors empirically showed that subtree features obtained by subtree mining, were able to improve the performance of Question Classification for boosting and maximum entropy models. In this paper, our first goal is to

Mystic

Data-Driven Approach Based on Semantic Roles for Recognizing Temporal Expressions and Events in Chiny stage and high-performance approaches are needed. Recently, in TempEval-2 evaluation exercise, corpora annotated in TimeML were released for different languages including Chinese. However, no systems were evaluated in this language. We present a data-driven approach for addressing these tasks in C

apiary

Abrade

烤架

OntoFIS as a NLP Resource in the Drug-Therapy Domain: Design Issues and Solutions Appliedral informational resources, semantically annotated, are under development. One of the existing development lines is oriented to reusing the effort spent on the design of the existing resources on the Web and obtaining knowledge-based resources for natural language processing (NLP) tasks. In this li

SEVER

paradigm

A System for Adaptive Information Extraction from Highly Informal Textes, classified ads, tweets, etc. It is built on a modular architecture that integrates in a transparent way off-the-shelf NLP tools, general procedures on strings and machine learning and processes tailored to a domain..The system is called adaptive because it implements a semi-supervised approach.

TRAWL