TY - GEN
T1 - ECNU at SemEval-2017 Task 5
T2 - 11th International Workshop on Semantic Evaluations, SemEval 2017, co-located with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017
AU - Jiang, Mengxiao
AU - Lan, Man
AU - Wu, Yuanbin
N1 - Publisher Copyright:
© 2017 Association for Computational Linguistics
PY - 2017
Y1 - 2017
N2 - This paper describes our systems submitted to the Fine-Grained Sentiment Analysis on Financial Microblogs and News task (i.e., Task 5) in SemEval-2017. This task includes two subtasks in microblogs and news headline domain respectively. To settle this problem, we extract four types of effective features, including linguistic features, sentiment lexicon features, domain-specific features and word embedding features. Then we employ these features to construct models by using ensemble regression algorithms. Our submissions rank 1st and rank 5th in subtask 1 and subtask 2 respectively.
AB - This paper describes our systems submitted to the Fine-Grained Sentiment Analysis on Financial Microblogs and News task (i.e., Task 5) in SemEval-2017. This task includes two subtasks in microblogs and news headline domain respectively. To settle this problem, we extract four types of effective features, including linguistic features, sentiment lexicon features, domain-specific features and word embedding features. Then we employ these features to construct models by using ensemble regression algorithms. Our submissions rank 1st and rank 5th in subtask 1 and subtask 2 respectively.
UR - https://www.scopus.com/pages/publications/85122560357
U2 - 10.18653/v1/S17-2152
DO - 10.18653/v1/S17-2152
M3 - 会议稿件
AN - SCOPUS:85122560357
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 888
EP - 893
BT - ACL 2017 - 11th International Workshop on Semantic Evaluations, SemEval 2017, Proceedings of the Workshop
PB - Association for Computational Linguistics (ACL)
Y2 - 3 August 2017 through 4 August 2017
ER -