This paper describes our contribution in Opinion Target Extraction OTE and Sentiment Polarity sub tasks of SemEval 2015 ABSA task. A CRF model with IOB notation has been adopted for OTE with several groups of features including syntactic, lexical, semantic, sentiment lexicon features. Our submission for OTE is ranked fifth over twenty submissions. A Logistic Regression model with a weighting sc...

Previous studies have shown that speakers of languages such as German, Spanish, and French reactivate the syntactic gender of the antecedent of a pronoun to license gender agreement. As syntactic gender is assumed to be stored in the lexicon, this has motivated the claim that pronouns in these languages reactivate the lexical entry of their antecedent noun. In contrast, in languages without syn...

We address the problem of answering new questions in community forums, by selecting suitable answers to already asked questions. We approach the task as an answer ranking problem, adopting a pairwise neural network architecture that selects which of two competing answers is better. We focus on the utility of the three types of similarities occurring in the triangle formed by the original questi...

This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based class...

This paper describes the systems submitted by the University of San Francisco (USF) to Semeval-2014 Task 4, Aspect Based Sentiment Analysis (ABSA), which provides labeled data in two domains, laptops and restaurants. For the constrained condition of both the aspect term extraction and aspect term polarity tasks, we take a supervised machine learning approach using a combination of lexical, synt...

Auditory attention is a highly complex mechanism that involves the process of low-level acoustic features of sound together with higher level cognitive rules. In this paper, a novel method that combines biologically inspired auditory attention cues with higher level lexical and syntactic information is proposed to model task-dependent influences on a given task. The feature maps are extracted f...

Background. Regulation events are of critical importance to researchers trying to understand processes in living beings. These events are naturally complex and can involve both individual molecular entities and other biomedical events. Of equal importance is the ability to capture statements that refer to regulation events that do not take place. In this paper we explore the identification of n...

This paper introduces the state-of-the-art MT evaluation survey that contains both manual and automatic evaluation methods. The traditional human evaluation criteria mainly include the intelligibility, fidelity, fluency, adequacy, comprehension, and informativeness. We classify the automatic evaluation methods into two categories, including lexical similarity and linguistic features application...