Papers with Code 아카이브
Suggestion mining
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
Suggestion mining can be defined as the extraction of suggestions from unstructured text,
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Near-Zero-Shot Suggestion Mining with a Little Help from WordNet
YNU-HPCC at SemEval-2020 Task 8: Using a Parallel-Channel Model for Memotion Analysis
Open Domain Suggestion Mining Leveraging Fine-Grained Analysis
Suggestion Mining from Online Reviews using ULMFiT
ThisIsCompetition at SemEval-2019 Task 9: BERT is unstable for out-of-domain samples
NL-FIIT at SemEval-2019 Task 9: Neural Model Ensemble for Suggestion Mining
Zoho at SemEval-2019 Task 9: Semi-supervised Domain Adaptation using Tri-training for Suggestion Mining
Helping each Other: A Framework for Customer-to-Customer Suggestion Mining using a Semi-supervised Deep Neural Network
Open Domain Suggestion Mining: Problem Definition and Datasets
Inducing Distant Supervision in Suggestion Mining through Part-of-Speech Embeddings
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.