S
Sabino Miranda-Jiménez
Researcher at Consejo Nacional de Ciencia y Tecnología
Publications - 42
Citations - 440
Sabino Miranda-Jiménez is an academic researcher from Consejo Nacional de Ciencia y Tecnología. The author has contributed to research in topics: Sentiment analysis & Task (project management). The author has an hindex of 11, co-authored 38 publications receiving 381 citations. Previous affiliations of Sabino Miranda-Jiménez include Instituto Politécnico Nacional.
Papers
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Book ChapterDOI
Empirical study of machine learning based approach for opinion mining in tweets
Grigori Sidorov,Sabino Miranda-Jiménez,Francisco Viveros-Jiménez,Alexander Gelbukh,Noé Alejandro Castro-Sánchez,Francisco Velasquez,Ismael Díaz-Rangel,Sergio Suárez-Guerra,Alejandro Treviño,Juan Gordon +9 more
TL;DR: This paper examines how classifiers work while doing opinion mining over Spanish Twitter data, and presents best settings of parameters for practical applications of opinion mining in Spanish Twitter.
Journal ArticleDOI
An automated text categorization framework based on hyperparameter optimization
TL;DR: A minimalistic and wide system able to tackle text classification tasks independent of domain and language, namely microTC is proposed, composed of some easy to implement text transformations, text representations, and a supervised learning algorithm that produces a competitive classifier even in the domain of informally written text.
Book ChapterDOI
Semantic Genetic Programming for Sentiment Analysis
TL;DR: A novel GP system, namely, Root Genetic Programming, is proposed, and previous genetic operators based on projections on the phenotype space are extended, and the results show that these systems are able to tackle this problem being competitive with other state-of-the-art classifiers.
Proceedings ArticleDOI
EvoDAG: A semantic Genetic Programming Python library
TL;DR: EvoDAG (Evolving Directed Acyclic Graph) is a Python library that implements a steady-state semantic Genetic Programming with tournament selection using an extension of the authors' previous crossover operators based on orthogonal projections in the phenotype space.
Latent Dirichlet Allocation complement in the vector space model for Multi-Label Text Classification
Jorge Victor Carrera Trejo,Grigori Sidorov,Sabino Miranda-Jiménez,Marco Antonio Moreno Ibarra,Rodrigo Cadena Martínez +4 more
TL;DR: This paper considers multi-label text classification task and applies various feature sets, using traditional tf-IDF values of the features and trying several combinations of features, like bigrams and unigrams.