The translation of sentiment information is a task from which sentiment analysis systems can benefit. We present a novel, graph-based approach using SimRank, a well-established ve...
Various text mining algorithms require the process of feature selection. High-level semantically rich features, such as figurative language uses, speech errors etc., are very prom...
We show that using confidence-weighted classification in transition-based parsing gives results comparable to using SVMs with faster training and parsing time. We also compare wit...
Tree SRL system is a Semantic Role Labelling supervised system based on a tree-distance algorithm and a simple k-NN implementation. The novelty of the system lies in comparing the...
This paper presents ongoing research on computational models for non-cooperative dialogue. We start by analysing different levels of cooperation in conversation. Then, inspired by...
Statistical systems with high accuracy are very useful in real-world applications. If these systems can capture basic linguistic information, then the usefulness of these statisti...
We tackle the previously unaddressed problem of unsupervised determination of the optimal morphological segmentation for statistical machine translation (SMT) and propose a segmen...
We present a probabilistic model extension to the Tesni`ere Dependency Structure (TDS) framework formulated in (Sangati and Mazza, 2009). This representation incorporates aspects ...
In this paper, we propose a novel method for automatic segmentation of a Sanskrit string into different words. The input for our segmentizer is a Sanskrit string either encoded as...
This work models Word Sense Disambiguation (WSD) problem as a Distributed Constraint Optimization Problem (DCOP). To model WSD as a DCOP, we view information from various knowledg...