activity
20162021
most citedModeling Noisiness to Recognize Named Entities using Multitask Neural Networks on Social Media

53 citations · 108 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL2021

Deep Bag-of-Sub-Emotions for Depression Detection in Social Media

Juan S. Lara, Mario Ezra Aragon, Fabio A. Gonzalez +1

This paper presents the Deep Bag-of-Sub-Emotions (DeepBoSE), a novel deep learning model for depression detection in social media. The model is formulated such that it internally c…

cs.CL2019

The performance evaluation of Multi-representation in the Deep Learning models for Relation Extraction Task

Jefferson A. Peña Torres, Raul Ernesto Gutierrez, Victor A. Bucheli +1

Single implementing, concatenating, adding or replacing of the representations has yielded significant improvements on many NLP tasks. Mainly in Relation Extraction where static, c…

cs.CL201953 cited

Modeling Noisiness to Recognize Named Entities using Multitask Neural Networks on Social Media

Gustavo Aguilar, A. Pastor López-Monroy, Fabio A. González +1

Recognizing named entities in a document is a key task in many NLP applications. Although current state-of-the-art approaches to this task reach a high performance on clean text (e…

cs.LG20194 cited

Quantum Latent Semantic Analysis

Fabio A. González, Juan C. Caicedo

The main goal of this paper is to explore latent topic analysis (LTA), in the context of quantum information retrieval. LTA is a valuable technique for document analysis and repres…

cs.CL2018

Letting Emotions Flow: Success Prediction by Modeling the Flow of Emotions in Books

Suraj Maharjan, Sudipta Kar, Manuel Montes-y-Gomez +2

Books have the power to make us feel happiness, sadness, pain, surprise, or sorrow. An author's dexterity in the use of these emotions captivates readers and makes it difficult for…

stat.ML201751 cited

Gated Multimodal Units for Information Fusion

John Arevalo, Thamar Solorio, Manuel Montes-y-Gómez +1

This paper presents a novel model for multimodal learning based on gated neural networks. The Gated Multimodal Unit (GMU) model is intended to be used as an internal unit in a neur…