In face processing tasks, prior presentation of internal facial features, when compared with external ones, facilitates the recognition of subsequently displayed familiar faces. In a previous ERP study (Olivares & Iglesias, 2010) we found a visibly larger N400-like effect when identity mismatch familiar faces were preceded by internal features, as compared to prior presentation of external ones...

This paper describes the methods we have employed to solve the author profiling task at PAN-2013. Our goal was to use simple features to identify the age group and the gender of the author of a given text. We introduce the features, detail how the classifiers were trained, and how the experiments were run.

While human observers are able to cope with variations in color and appearance of histological stains, digital pathology algorithms commonly require a wellnormalized setting to achieve peak performance, especially when a limited amount of labeled data is available. This work provides a fully automated, end-to-end learning-based setup for normalizing histological stains, which considers the text...

The effectiveness of audio content analysis for music retrieval may be enhanced by the use of available metadata. In the present work, observed differences in singing style and instrumentation across genres are used to adapt acoustic features for the singing voice detection task. Timbral descriptors traditionally used to discriminate singing voice from accompanying instruments are complemented ...

We report a new approach of using statistical context-based scores as encoded features to train neural networks to achieve secondary structure prediction accuracy improvement. The context-based scores are pseudo-potentials derived by evaluating statistical, high-order inter-residue interactions, which estimate the favorability of a residue adopting certain secondary structure conformation withi...

There is a growing body of work studying suicide ideation, expressions of intentions to kill oneself, on social media. We explore the problem of detecting such ideation on Twitter, focusing on the impact of a set of features drawn from the literature and on the role of discussion context for this task. Our experiments show a significant improvement upon the previously published results for the ...

Sentiment lexicons have been leveraged as a useful source of features for sentiment analysis models, leading to the state-of-the-art accuracies. On the other hand, most existing methods use sentiment lexicons without considering context, typically taking the count, sum of strength, or maximum sentiment scores over the whole input. We propose a context-sensitive lexicon-based method based on a s...

The representation of information plays the key role in searching a document. While for text documents it is simple to extract keywords to find a document, for images this task is more challenging. In this paper we discuss different representations of images, point out their advantages and disadvantages and present our proposed method for stable and reliable information extraction to address th...

We test a method of clustering dialects of English according to patterns of shared phonological features. Previous linguistic research has generally considered phonological features as independent of each other, but context is important: rather than considering each phonological feature individually, we compare the patterns of shared features, or Mutual Information (MI). The dependence of one p...

Chinese abbreviations are frequently used without being defined, which has brought much difficulty into NLP. In this study, the definitionindependent abbreviation identification problem is proposed and resolved as a classification task in which abbreviation candidates are classified as either ‘abbreviation’ or ‘non-abbreviation’ according to the posterior probability. To meet our aim of identif...