paper-with-me

홈 › Papers

HITSZ-ICRC: Exploiting Classification Approach for Answer Selection in Community Question Answering

2015-06-01 · SEMEVAL 2015 6 · Yongshuai Hou, Cong Tan, Xiaolong Wang, Yaoyun Zhang, Jun Xu, Qingcai Chen
📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

Answer SelectionCommunity Question AnsweringGeneral ClassificationQuestion Answering

Similar Papers 제목 키워드 기반

HITSZ-ICRC: An Integration Approach for QA TempEval Challenge

2015-06-01 · SEMEVAL 2015 6 · Yongshuai Hou, Cong Tan, Qingcai Chen, Xiaolong Wang
Information RetrievalQuestion Answering

HITSZ-ICRC: A Report for SMM4H Shared Task 2020-Automatic Classification of Medications and Adverse Effect in Tweets

2020-12-01 · SMM4H (COLING) 2020 12 · Xiaoyu Zhao, Ying Xiong, Buzhou Tang

This is the system description of the Harbin Institute of Technology Shenzhen (HITSZ) team for the first and second subtasks of the fifth Social Media Mining for Health Applications (SMM4H) shared task in 2020. The first…

ClassificationTask 2

HITSZ-ICRC: A Report for SMM4H Shared Task 2019-Automatic Classification and Extraction of Adverse Effect Mentions in Tweets

2019-08-01 · WS 2019 8 · Shuai Chen, Yuanhang Huang, Xiaowei Huang, Haoming Qin 외

This is the system description of the Harbin Institute of Technology Shenzhen (HITSZ) team for the first and second subtasks of the fourth Social Media Mining for Health Applications (SMM4H) shared task in 2019. The two …

ICRC-HIT: A Deep Learning based Comment Sequence Labeling System for Answer Selection Challenge

2015-06-01 · SEMEVAL 2015 6 · Xiaoqiang Zhou, Baotian Hu, Jiaxin Lin, Yang Xiang 외
Answer SelectionCommunity Question AnsweringFeature EngineeringInformation Retrieval+2

LCSTS: A Large Scale Chinese Short Text Summarization Dataset

2015-06-19 · EMNLP 2015 9 · Baotian Hu, Qingcai Chen, Fangze Zhu

Automatic text summarization is widely regarded as the highly difficult problem, partially because of the lack of large text summarization data set. Due to the great challenge of constructing the large scale summaries fo…

Text Summarization