Agent AI for Finance (Запис № 579206)

МАРК-запис
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001 - CONTROL NUMBER
control field 978-3-031-94687-5
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250902150252.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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fixed length control field 250717s2025 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031946875
-- 978-3-031-94687-5
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-031-94687-5
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q334-342
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA347.A78
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Chen, Chung-Chi.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
9 (RLIN) 7981
245 10 - TITLE STATEMENT
Title Agent AI for Finance
Medium [electronic resource] :
Remainder of title From Financial Argument Mining to Agent-Based Modeling /
Statement of responsibility, etc by Chung-Chi Chen, Hiroya Takamura.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2025.
264 #1 -
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-- Springer Nature Switzerland :
-- Imprint: Springer,
-- 2025.
300 ## - PHYSICAL DESCRIPTION
Extent XII, 83 p. 9 illus., 8 illus. in color.
Other physical details online resource.
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490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics,
Міжнародний стандартний серійний номер для назви серії (ISSN) 2196-5498
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Preface -- 1. Introduction -- 2. Financial Argument Mining -- 3. Single-Agent/Model Design -- 4. Multi-Agent Interaction -- 5. Multi-Scale Model Synergy -- 6. Generative AI Application Scenarios -- 7. Looking to the Future.
506 0# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Open Access
520 ## - SUMMARY, ETC.
Summary, etc This open access book provides an overview of the current state of financial argument mining and financial text generation, and presents the authors’ thoughts on the blueprint for NLP in finance in the agent AI era. Financial documents contain numerous causal inferences and subjective opinions. In a previous book, “From Opinion Mining to Financial Argument Mining” (Springer, 2021), the first author discussed understanding financial documents in a fine-grained manner, particularly those containing opinions. The book highlighted several future directions, such as financial argument mining, multimodal opinion understanding, and analysis generation, and anticipated a lengthy journey for these topics. However, since 2022, ChatGPT and large language models (LLMs) have shown promising advancements, motivating the authors to write this second book on the topic of financial Natural Language Processing (NLP). Agent-based AI systems have been widely discussed since the advent of LLMs. This book aims to equip researchers and practitioners with the latest methodologies, concepts, and frameworks for developing, deploying, and evaluating AI agents with capabilities in multimodal understanding, decision-making, and interaction. It places a special emphasis on human-centered decision-making and multi-agent cooperation in financial applications. The book surveys the current landscape and discuss future research and development directions. Targeting a wide audience, from students to seasoned researchers in AI and finance, this book offers an overview of recent trends in Agent AI for finance. It provides a foundation for students to understand the field and design their research direction, while inviting experienced researchers to engage in discussions on open research questions informed by pilot experimental results. Although this book focuses on financial applications, the discussed concepts and methods can also be applied to other real-world applications by integrating domain-specific characteristics. The authors look forward to seeing new findings and more novel extensions based on the proposed ideas.
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-- Accessibility summary: This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. Please note that a more accessible version of this eBook is available as ePub.
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650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Multiagent systems.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Business
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Business information services.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Natural language processing (Computer science).
9 (RLIN) 1334
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Multiagent Systems.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Business Analytics.
9 (RLIN) 21719
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Business Information Systems.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Natural Language Processing (NLP).
9 (RLIN) 1340
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Takamura, Hiroya.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
9 (RLIN) 21720
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031946868
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031946882
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title SpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics,
-- 2196-5498
9 (RLIN) 5992
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-031-94687-5">https://doi.org/10.1007/978-3-031-94687-5</a>
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