https://scholars.lib.ntu.edu.tw/handle/123456789/581356
標題: | FinSense: An Assistant System for Financial Journalists and Investors | 作者: | Liou Y.-T Chen C.-C Tang T.-H Huang H.-H HSIN-HSI CHEN |
關鍵字: | Convolutional neural networks; Decision making; Finance; Information retrieval; Websites; Convolutional networks; Financial news; Working efficiency; Data mining | 公開日期: | 2021 | 起(迄)頁: | 882-885 | 來源出版物: | WSDM 2021 - Proceedings of the 14th ACM International Conference on Web Search and Data Mining | 摘要: | This paper demonstrates FinSense, a system that improves the working efficiency of financial information processing. Given the draft of a financial news story, FinSense extracts the explicit-mentioned stocks and further infers the implicit stocks, providing insightful information for decision making. We propose a novel graph convolutional network model that performs implicit financial instrument inference toward the in-domain data. In addition, FinSense generates candidate headlines for the draft, reducing a significant amount of time in journalism production. The proposed system also provides assistance to investors to sort out the information in the financial news articles. ? 2021 Owner/Author. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103057947&doi=10.1145%2f3437963.3441704&partnerID=40&md5=fa8301d865aa0265cd888ed8e5fb8fa3 https://scholars.lib.ntu.edu.tw/handle/123456789/581356 |
DOI: | 10.1145/3437963.3441704 |
顯示於: | 資訊工程學系 |
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