In this work, we have presented a novel method for detection of retinal image features, the optic disc and the fovea, from colour fundus photographs of dilated eyes for Computeraided Diagnosis(CAD) system. A saliency map based method was used to detect the optic disc followed by an unsupervised probabilistic Latent Semantic Analysis for detection validation. The validation concept is based on d...

We present a novel approach to automatic metaphor identification in unrestricted text. Starting from a small seed set of manually annotated metaphorical expressions, the system is capable of harvesting a large number of metaphors of similar syntactic structure from a corpus. Our method is distinguished from previous work in that it does not employ any hand-crafted knowledge, other than the init...

The topic of clustering has been widely studied in the field of Data Analysis, where it is defined as an unsupervised process of grouping objects together based on notions of similarity. Clustering in the field of Multi-Criteria Decision Aid (MCDA) has seen a few adaptations of methods from Data Analysis, most of them however using concepts native to that field, such as the notions of similarit...

We present the approach followed by INESCID in the SemEval 2015 Twitter Sentiment Analysis challenge, subtask E. The goal was to determine the strength of the association of Twitter terms with positive sentiment. Using two labeled lexicons, we trained a regression model to predict the sentiment polarity and intensity of words and phrases. Terms were represented as word embeddings induced in an ...

In knowledge discovery from collected databases, one of the firstly arising questions is ”what should be discovered”. Two lines of work can be followed. In the first line, unsupervised learning is performed, usually clustering data, followed by a characterization of the discovered knowledge. In the second line, classifiers are constructed for each highly important feature registered in the data...

This study implements a vector space model approach to measure the sentiment orientations of words. Two representative vectors for positive/negative polarity are constructed using high-dimensional vector space in both an unsupervised and a semisupervised manner. A sentiment orientation value per word is determined by taking the difference between the cosine distances against the two reference v...