arXiv:1811.11569
Document classification using a Bi-LSTM to unclog Brazil's supreme court
원문 초록
The Brazilian court system is currently the most clogged up judiciary system in the world. Thousands of lawsuit cases reach the supreme court every day. These cases need to be analyzed in order to be associated to relevant tags and allocated to the right team. Most of the cases reach the court as raster scanned documents with widely variable levels of quality. One of the first steps for the analysis is to classify these documents. In this paper we present a Bidirectional Long Short-Term Memory network (Bi-LSTM) to classify these pieces of legal document.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Incorporating Interpretability into Latent Factor Models via Fast Influence Analysis
Can Reasoning LLMs Enhance Clinical Document Classification?
Text Chunking for Document Classification for Urban System Management using Large Language Models
Evaluating Negative Sampling Approaches for Neural Topic Models
Converting Transformers into DGNNs Form
Cross-Entropy Attacks to Language Models via Rare Event Simulation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.