LIPI at the FinNLP-2022 ERAI Task: Ensembling Sentence Transformers for Assessing Maximum Possible Profit and Loss from Online Financial Posts

Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP) Pub Date : 1900-01-01 DOI:10.18653/v1/2022.finnlp-1.13

Sohom Ghosh, S. Naskar

引用次数: 1

Abstract

Using insights from social media for making investment decisions has become mainstream. However, in the current era of information ex- plosion, it is essential to mine high-quality so- cial media posts. The FinNLP-2022 ERAI task deals with assessing Maximum Possible Profit (MPP) and Maximum Loss (ML) from social me- dia posts relating to finance. In this paper, we present our team LIPI’s approach. We ensem- bled a range of Sentence Transformers to quan- tify these posts. Unlike other teams with vary- ing performances across different metrics, our system performs consistently well. Our code is available here https://github.com/sohomghosh/LIPI_ERAI_ FinNLP_EMNLP- 2022/

查看原文本刊更多论文

LIPI在FinNLP-2022 ERAI任务:集成句子变形以评估在线金融帖子的最大可能利润和损失

利用社交媒体的见解来做投资决策已经成为主流。然而，在当今信息爆炸的时代，挖掘高质量的社交媒体帖子是必不可少的。FinNLP-2022 ERAI任务涉及评估与金融相关的社交媒体帖子的最大可能利润(MPP)和最大可能损失(ML)。在本文中，我们介绍了我们的团队LIPI的方法。我们使用了一系列的句子转换器来完善这些帖子。不像其他团队在不同的指标上有不同的表现，我们的系统一直表现良好。我们的代码可以在这里获得https://github.com/sohomghosh/LIPI_ERAI_ FinNLP_EMNLP- 2022/

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)

自引率

0.00%

发文量