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政大機構典藏 > 資訊學院 > 資訊科學系 > 會議論文 > Item 140.119/137222

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/137222

Title:	MIG at the NTCIR-15 FinNum-2 Task: Use the transfer learning and feature engineering for numeral attachment task
Authors:	劉昭麟 Liu, Chao-Lin Chen, Yu-Yu
Contributors:	資科系
Keywords:	Numeral attachment;financial social media;transfer learning;feature engineering
Date:	2020-12
Issue Date:	2021-09-22 10:39:33 (UTC+8)
Abstract:	In the FinNum-2 task, the goal is to judge whether the specified numeral is related to the given stock symbol in a financial tweet. We employ a transfer-learning mechanism and the Google BERT embeddings so that we only need to collect and annotate a small amount of data to train the classifiers for the task. In addition, our classifiers consider some intuitive but useful syntactic features, e.g., the positions of words in the tweets. Experimental results indicate that these new features boost the prediction quality, and we achieved better than 68% in the tests in the formal run.
Relation:	NTCIR-15 Proceedings, NII, Japan, pp.79‒82
Data Type:	conference
Appears in Collections:	[資訊科學系] 會議論文

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