From Opinion Mining to Financial Argument Mining
暫譯: 從意見挖掘到金融論證挖掘
Chen, Chung-Chi, Huang, Hen-Hsen, Chen, Hsin-Hsi
- 出版商: Springer
- 出版日期: 2021-05-21
- 售價: $1,780
- 貴賓價: 9.5 折 $1,691
- 語言: 英文
- 頁數: 95
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9811628807
- ISBN-13: 9789811628801
海外代購書籍(需單獨結帳)
商品描述
Opinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most of the researches on this topic only focus on the coarse-grained market sentiment analysis, i.e., 2-way classification for bullish/bearish. Thanks to the recent financial technology (FinTech) development, some interdisciplinary researchers start to involve in the in-depth analysis of investors' opinions. These works indicate the trend toward fine-grained opinion mining in the financial domain.
When expressing opinions in finance, terms like bullish/bearish often spring to mind. However, the market sentiment of the financial instrument is just one type of opinion in the financial industry. Like other industries such as manufacturing and textiles, the financial industry also has a large number of products. Financial services are also a major business for many financial companies, especially in the context of the recent FinTech trend. For instance, many commercial banks focus on loans and credit cards. Although there are a variety of issues that could be explored in the financial domain, most researchers in the AI and NLP communities only focus on the market sentiment of the stock or foreign exchange.
This open access book addresses several research issues that can broaden the research topics in the AI community. It also provides an overview of the status quo in fine-grained financial opinion mining to offer insights into the futures goals. For a better understanding of the past and the current research, it also discusses the components of financial opinions one-by-one with the related works and highlights some possible research avenues, providing a research agenda with both micro- and macro-views toward financial opinions.商品描述(中文翻譯)
意見挖掘是許多領域中普遍的研究議題。然而，在金融領域，它仍處於早期階段。大多數關於這個主題的研究僅專注於粗粒度的市場情緒分析，即對於看漲/看跌的二元分類。隨著近期金融科技（FinTech）的發展，一些跨學科的研究者開始參與對投資者意見的深入分析。這些研究顯示出金融領域中對於細粒度意見挖掘的趨勢。
在金融領域表達意見時，像是看漲（bullish）/看跌（bearish）等術語常常浮現在腦海中。然而，金融工具的市場情緒僅是金融行業中一種意見。與製造業和紡織業等其他行業類似，金融行業也擁有大量的產品。金融服務對於許多金融公司來說也是一項主要業務，尤其是在近期的金融科技趨勢下。例如，許多商業銀行專注於貸款和信用卡。儘管在金融領域中有許多問題可以探討，但人工智慧（AI）和自然語言處理（NLP）社群中的大多數研究者僅專注於股票或外匯的市場情緒。
這本開放存取的書籍針對幾個研究議題，旨在擴展AI社群中的研究主題。它還提供了細粒度金融意見挖掘的現狀概述，以提供對未來目標的見解。為了更好地理解過去和當前的研究，它逐一討論金融意見的組成部分及相關工作，並突顯一些可能的研究方向，提供一個包含微觀和宏觀視角的金融意見研究議程。
作者簡介
Chung-Chi Chen is a Ph.D. candidate in the Department of Computer Science and Information Engineering at National Taiwan University and a lecturer in the Department of Quantitative Finance, National Tsing Hua University. His research focuses on financial opinion mining and numeral understanding. He is the organizer of FinNum shared task series in NTCIR (2018-2020) and the FinNLP workshop series in IJCAI (2019-2020). He won the 1st prize in both the Jih Sun & Microsoft FinTech Hackathon (2019) and the Standard Chartered FinTech competition (2018) and the 2nd prize in both the Jih Sun & Microsoft FinTech Hackathon (2018) and the E.SUN FHC FinTech Hackathon (2017).
Hen-Hsen Huang received the Ph.D. degree in Computer Science and Information Engineering from National Taiwan University, Taiwan. Dr. Huang is currently an assistant professor in the Department of Computer Science at National Chengchi University. His research interests include natural language processing, computational linguistics, and information retrieval. His work has been published in SCI/SSCI journals and international conferences, including WWW, IJCAI, ACL, CIKM, and COLING. Dr. Huang's award and honors include the Honorable Mention of Doctoral Dissertation Award of ACLCLP in 2014 and the Honorable Mention of Master Thesis Award of ACLCLP in 2008. He serves as the registration chair of TAAI 2017, and as PC members of ACL2018, NAACL 2018, ACL 2017, COLING 2016, NAACL 2016, and ACL 2015, and will be general co-chair of SIGIR 2023.
Hsin-Hsi Chen received the Ph.D. degree in electrical engineering in 1988 from National Taiwan University, Taiwan. He is a distinguished professor in Department of Computer Science and Information Engineering, National Taiwan University. His research interests are natural language processing, information retrieval and extraction, and web mining. Dr. Chen served as senior PC members of ACM SIGIR 2006, 2007, 2008 and 2009, area/track chairs of AAAI 2020, AACL 2020, EMNLP 2018, ACL 2012, ACL-IJCNLP 2009 and ACM CIKM 2008, and PC members of many conferences. He received Google research awards in 2007 and 2012, awards of Microsoft Research Asia in 2008 and 2009, MOST Outstanding Research Award in 2017, and the AmTRAN Chair Professorship in 2018.
作者簡介(中文翻譯)
鄭中基（Chung-Chi Chen）是國立台灣大學計算機科學與資訊工程學系的博士候選人，同時也是國立清華大學定量金融學系的講師。他的研究專注於金融意見挖掘和數字理解。他是NTCIR（2018-2020）中FinNum共享任務系列和IJCAI（2019-2020）中FinNLP研討會系列的組織者。他在2019年的日盛與微軟金融科技黑客松（Jih Sun & Microsoft FinTech Hackathon）中獲得第一名，並在2018年的渣打金融科技競賽（Standard Chartered FinTech competition）中獲得第一名，此外，他在2018年的日盛與微軟金融科技黑客松中獲得第二名，以及在2017年的玉山金融科技黑客松（E.SUN FHC FinTech Hackathon）中獲得第二名。
黃亨賢（Hen-Hsen Huang）於國立台灣大學獲得計算機科學與資訊工程博士學位。黃博士目前是國立政治大學計算機科學系的助理教授。他的研究興趣包括自然語言處理、計算語言學和資訊檢索。他的研究成果已發表於SCI/SSCI期刊及國際會議，包括WWW、IJCAI、ACL、CIKM和COLING。黃博士的獎項和榮譽包括2014年ACLCLP博士論文獎的榮譽提名和2008年ACLCLP碩士論文獎的榮譽提名。他曾擔任2017年TAAI的註冊主席，並擔任ACL2018、NAACL 2018、ACL 2017、COLING 2016、NAACL 2016和ACL 2015的程序委員，並將擔任2023年SIGIR的共同主席。
陳信熙（Hsin-Hsi Chen）於1988年在國立台灣大學獲得電機工程博士學位。他是國立台灣大學計算機科學與資訊工程學系的特聘教授。他的研究興趣包括自然語言處理、資訊檢索與提取以及網路挖掘。陳博士曾擔任ACM SIGIR 2006、2007、2008和2009的高級程序委員，AAAI 2020、AACL 2020、EMNLP 2018、ACL 2012、ACL-IJCNLP 2009和ACM CIKM 2008的區域/主題主席，以及多個會議的程序委員。他於2007年和2012年獲得Google研究獎，2008年和2009年獲得微軟亞洲研究院獎，2017年獲得科技部傑出研究獎，並於2018年獲得AmTRAN講座教授職位。
