3 citations · 6 across the 4 of their papers we have counts for
7 papers
A Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews
Edison Marrese-Taylor, Cristian Rodriguez-Opazo, Jorge A. Balazs +2
Despite the recent advances in opinion mining for written reviews, few works have tackled the problem on other sources of reviews. In light of this issue, we propose a multi-modal…
Gating Mechanisms for Combining Character and Word-level Word Representations: An Empirical Study
Jorge A. Balazs, Yutaka Matsuo
In this paper we study how different ways of combining character and word-level representations affect the quality of both final word and sentence representations. We provide stron…
Deep contextualized word representations for detecting sarcasm and irony
Suzana Ilić, Edison Marrese-Taylor, Jorge A. Balazs +1
Predicting context-dependent and non-literal utterances like sarcastic and ironic expressions still remains a challenging task in NLP, as it goes beyond linguistic patterns, encomp…
IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations
Jorge A. Balazs, Edison Marrese-Taylor, Yutaka Matsuo
In this paper we describe our system designed for the WASSA 2018 Implicit Emotion Shared Task (IEST), which obtained 2 place out of 26 teams with a test macro F1 scor…
IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets
Edison Marrese-Taylor, Suzana Ilic, Jorge A. Balazs +2
In this paper we introduce our system for the task of Irony detection in English tweets, a part of SemEval 2018. We propose representation learning approach that relies on a multi-…
Mining fine-grained opinions on closed captions of YouTube videos with an attention-RNN
Edison Marrese-Taylor, Jorge A. Balazs, Yutaka Matsuo
Video reviews are the natural evolution of written product reviews. In this paper we target this phenomenon and introduce the first dataset created from closed captions of YouTube…