arXiv:1710.09589
공식 코드 · Papers with Code
ALL-IN-1: Short Text Classification with One Model for All Languages
원문 초록
We present ALL-IN-1, a simple model for multilingual text classification that does not require any parallel data. It is based on a traditional Support Vector Machine classifier exploiting multilingual word embeddings and character n-grams. Our model is simple, easily extendable yet very effective, overall ranking 1st (out of 12 teams) in the IJCNLP 2017 shared task on customer feedback analysis in four languages: English, French, Japanese and Spanish.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Specialized text classification: an approach to classifying Open Banking transactions
A Hybrid Classification Approach using Topic Modeling and Graph Convolution Networks
PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification
Making Language Model a Hierarchical Classifier and Generator
Is Diversity All You Need for Scalable Robotic Manipulation?
Robustness of Misinformation Classification Systems to Adversarial Examples Through BeamAttack
토론
이 논문과 연결된 포럼 글이 아직 없습니다.