INGEOTEC at SemEval 2017 Task 4: A B4MSA Ensemble based on Genetic Programming for Twitter Sentiment Analysis

2017-08-01 · SEMEVAL 2017 8 · Mir, Sabino a-Jim{\'e}nez, Mario Graff, Eric Sadit Tellez, Daniela Moctezuma

This paper describes the system used in SemEval-2017 Task 4 (Subtask A): Message Polarity Classification for both English and Arabic languages. Our proposed system is an ensemble of two layers, the first one uses our generic framework for multilingual polarity classification (B4MSA) and the second layer combines all the decision function values predicted by B4MSA systems using a non-linear function evolved using a Genetic Programming system, EvoDAG. With this approach, the best performances reached by our system were macro-recall 0.68 (English) and 0.477 (Arabic) which set us in sixth and fourth positions in the results table, respectively.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

ClassificationCombinatorial OptimizationGeneral Classification Sentiment AnalysisTwitter Sentiment Analysis

INGEOTEC at SemEval-2019 Task 5 and Task 6: A Genetic Programming Approach for Text Classification

2019-06-01 · SEMEVAL 2019 6 · Mario Graff, Mir, Sabino a-Jim{\'e}nez, Eric Tellez 외

This paper describes our participation in HatEval and OffensEval challenges for English and Spanish languages. We used several approaches, B4MSA, FastText, and EvoMSA. Best results were achieved with EvoMSA, which is a m…

General Classification text-classification Text Classification

INGEOTEC at SemEval-2018 Task 1: EvoMSA and μTC for Sentiment Analysis

2018-06-01 · SEMEVAL 2018 6 · Mario Graff, Mir, Sabino a-Jim{\'e}nez, Eric S. Tellez 외

This paper describes our participation in Affective Tweets task for emotional intensity and sentiment intensity subtasks for English, Spanish, and Arabic languages. We used two approaches, μTC and EvoMSA. The first one i…

Combinatorial Optimization regression Sentiment Analysis Text Categorization

INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive Text

2020-12-01 · SEMEVAL 2020 · Sabino Miranda-Jim{\'e}nez, Eric S. Tellez, Mario Graff, Daniela Moctezuma

This paper describes our participation in OffensEval challenges for English, Arabic, Danish, Turkish, and Greek languages. We used several approaches, such as μTC, TextCategorization, and EvoMSA. Best results were achiev…

text-classification Text Classification

TakeLab at SemEval-2016 Task 6: Stance Classification in Tweets Using a Genetic Algorithm Based Ensemble

2016-06-01 · SEMEVAL 2016 6 · Martin Tutek, Ivan Sekuli{\'c}, Paula Gombar, Ivan Paljak 외

General Classification Stance Classification Stance Detection

Integer-Programming Ensemble of Temporal-Relations Classifiers

2014-12-05 · Catherine Kerr, Terri Hoare, Paula Carroll, Jakub Marecek

The extraction and understanding of temporal events and their relations are major challenges in natural language processing. Processing text on a sentence-by-sentence or expression-by-expression basis often fails, in par…

Sentence