Search Results for author: Jorge A. Balazs

Found 8 papers, 5 papers with code

A Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews

no code implementations WS 2020 Edison Marrese-Taylor, Cristian Rodriguez-Opazo, Jorge A. Balazs, Stephen Gould, Yutaka Matsuo

Despite the recent advances in opinion mining for written reviews, few works have tackled the problem on other sources of reviews.

Opinion Mining

Gating Mechanisms for Combining Character and Word-level Word Representations: An Empirical Study

1 code implementation NAACL 2019 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.

Semantic Similarity Semantic Textual Similarity +1

Deep contextualized word representations for detecting sarcasm and irony

1 code implementation WS 2018 Suzana Ilić, Edison Marrese-Taylor, Jorge A. Balazs, Yutaka Matsuo

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, encompassing common sense and shared knowledge as crucial components.

Common Sense Reasoning

IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations

1 code implementation WS 2018 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$^{\text{nd}}$ place out of 26 teams with a test macro F1 score of $0. 710$.

Emotion Classification General Classification

Mining fine-grained opinions on closed captions of YouTube videos with an attention-RNN

1 code implementation WS 2017 Edison Marrese-Taylor, Jorge A. Balazs, Yutaka Matsuo

These results, as well as further experiments on domain adaptation for aspect extraction, suggest that differences between speech and written text, which have been discussed extensively in the literature, also extend to the domain of product reviews, where they are relevant for fine-grained opinion mining.

Aspect Extraction Domain Adaptation +2

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