Shakery, "Emad at SemEval-2019 task 6: offensive language identification using traditional machine learning and deep learning approaches," Proc. Pedersen, "Duluth at SemEval-2019 task 6: Lexical approaches to identify and categorize offensive tweets," arXiv preprint arXiv:2007.12949, 2019. 13th International Workshop on SemEval, pp. Rosso, "DeepAnalyzer at SemEval-2019 Task 6: A deep learning-based ensemble method for identifying offensive tweets," Proc. Patel, "DA-LD-Hildesheim at SemEval-2019 task 6: tracking offensive content with deep learning using shallow representation," Proc. Androutsopoulos, "Convai at semeval-2019 task 6: Offensive language identification and categorization with perspective and bert," Proc. T at SemEval-2019 Task 6: Offensive Language Identification Based on BiLSTM with Double Attention," Proc. Buttery, "CAMsterdam at SemEval-2019 Task 6: Neural and graph-based feature extraction for the identification of offensive tweets," Proc. Fong, "Bnu-hkbu uic nlp team 2 at semeval-2019 task 6: Detecting offensive language using bert model," Proc. Chennuru, "bhanodaig at SemEval-2019 Task 6: Categorizing offensive language in social media," Proc. Swapna, "Amrita School of Engineering-CSE at SemEval-2019 Task 6: Manipulating attention with temporal convolutional neural network for offense identification and classification," Proc. Biton, "Amobee at SemEval-2019 Tasks 5 and 6: Multiple choice over contextual embedding," arXiv preprint arXiv:1904.08292., 2019. Kumar, " Predicting the Type and Target of Offensive Posts in Social Media," Proc. Hussain, "Comparing Oversampling Techniques to Handle the Class Imbalance Problem: A Customer Churn Prediction Case Study," IEEE Access, vol.
Elor, "AE-SMOTE: A Multi-Modal Minority Oversampling Framework," pp. Pacific-Asia conference on knowledge discovery and data mining, pp. Lursinsap, "Safe-Level-SMOTE: Safe-Level-Synthetic Minority Over-Sampling TEchnique for Handling the Class Imbalanced Problem," Proc. Last, "Improving imbalanced learning through a heuristic over-sampling method based on k-means and SMOTE," Inf.
Köse Ulukök, " HCAB SMOTE: A Hybrid Clustered Afnitive Borderline SMOTE Approach for Imbalanced Data Binary Classifcation," Arab. Kegelmeyer, "SMOTE: Synthetic Minority Over-sampling Technique," J Artif Intell Res., vol. Borrajo, " An HMM-based over-sampling technique to improve text classification," Expert Syst. 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. Sardana, "Handling Class Imbalance Problem using Oversampling Techniques: A Review," Proc. Zhu, " Ponzi scheme detection via oversampling-based Long Short-Term Memory for smart contracts," Knowl Based Syst., vol. Ju, "Imbalanced classification is one of most popular topics in the field of machine learning," Big Data Res., vol. Brownlee, Imbalanced Classification with Python. 2006 IEEE International Conference on Granular Computing, pp. Zhang, "Granular SVM with Repetitive Undersampling for Highly Imbalanced Protein Homology Prediction," Proc. 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection, pp. Hajj, "Multi-Task Learning using AraBert for Offensive Language Detection," Proc. Sevim, "Improve Offensive Language Detection with Ensemble Classifiers," IJISAE, vol. Darwish K., "Arabic Offensive Language Classification on Twitter," Lecture Notes in Computer Science. Biemann, "Transfer Learning from LDA to BiLSTM-CNN for Offensive Language Detection in Twitter," arXiv preprint arXiv:1811.02906v1, 2018. Nakov, "OLID: A Large-Scale Semi-Supervised Dataset for Offensive Language Identification," arXiv preprint arXiv:2004.14454, 2020.
0 kommentar(er)
