{"type":"ScholarlyArticle","title":"F-HMTC: Detecting Financial Events for Investment Decisions Based on Neural Hierarchical Multi-Label Text Classification","authors":[{"name":"Xin Liang","slug":"xin-liang","given":"Xin","family":"Liang","affiliation":"Shanghai Engineering Research Center on Big Data Management System , Shanghai , China; School of Data Science and Engineering , East China Normal University , Shanghai , China"},{"name":"Dawei Cheng","slug":"dawei-cheng","given":"Dawei","family":"Cheng","affiliation":"Department of Computer Science and Engineering , Shanghai Jiao Tong University , Shanghai , China; SeekData Inc. , Shanghai , China"},{"name":"Fangzhou Yang","slug":"fangzhou-yang","given":"Fangzhou","family":"Yang","affiliation":"SeekData Inc. , Shanghai , China"},{"name":"Yifeng Luo","slug":"yifeng-luo","given":"Yifeng","family":"Luo","affiliation":"Shanghai Engineering Research Center on Big Data Management System , Shanghai , China; School of Data Science and Engineering , East China Normal University , Shanghai , China"},{"name":"Weining Qian","slug":"weining-qian","given":"Weining","family":"Qian","affiliation":"Shanghai Engineering Research Center on Big Data Management System , Shanghai , China; School of Data Science and Engineering , East China Normal University , Shanghai , China"},{"name":"Aoying Zhou","slug":"aoying-zhou","given":"Aoying","family":"Zhou","affiliation":"Shanghai Engineering Research Center on Big Data Management System , Shanghai , China; School of Data Science and Engineering , East China Normal University , Shanghai , China"}],"abstract":"The share prices of listed companies in the stock trading market are prone to be influenced by various events. Performing event detection could help people to timely identify investment risks and opportunities accompanying these events. The financial events inherently present hierarchical structures, which could be represented as tree-structured schemes in real-life applications, and detecting events could be modeled as a hierarchical multi-label text classification problem, where an event is designated to a tree node with a sequence of hierarchical event category labels. Conventional hierarchical multi-label text classification methods usually ignore the hierarchical relationships existing in the event classification scheme, and treat the hierarchical labels associated with an event as uniform labels, where correct or wrong label predictions are assigned with equal rewards or penalties. In this paper, we propose a neural hierarchical multi-label text classification method, namely F-HMTC, for a financial application scenario with massive event category labels. F-HMTC learns the latent features based on bidirectional encoder representations from transformers, and directly maps them to hierarchical labels with a delicate hierarchy-based loss layer. We conduct extensive experiments on a private financial dataset with elaborately-annotated labels, and F-HMTC consistently outperforms state-of-art baselines by substantial margins. We will release both the source codes and dataset on the first author's repository.","doi":"10.24963/ijcai.2020/619","url":"https://ijcai.org/proceedings/2020/619","pdf":"https://ijcai.org/proceedings/2020/0619.pdf","markdown":"https://ijcai.org/proceedings/2020/619.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/619","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Special Track on AI in FinTech","track":"Special Track on AI in FinTech","number":619,"pages":{"first":4490,"last":4496},"keywords":["Foundation for AI in FinTech: Deep learning and representation for FinTech","Foundation for AI in FinTech: Data mining and knowledge discovery for FinTech"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/24687/file_24687.m3u8","length_sec":294,"provider":"hls"}],"references":[{"position":1,"raw":"[Aggarwal and Zhai, 2012] Charu C Aggarwal and ChengX- iang Zhai. 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