[jsai-fin 0231] The AAAI-22 Workshop on Knowledge Discovery from Unstructured Data in Financial Services (KDF ‘22) - Deadline: 11/12/2021

[水田孝信]

みなさま、

来年２月に開催されるAAAIのワークショップです。
詳細は以下のメールや
<https://aaai-kdf.github.io/kdf2022/>
をご覧ください。

水田孝信 <https://mizutatakanobu.com/jindex.htm>
レポート書いてます！<https://www.sparx.co.jp/report/special/>


---------- Forwarded message ---------
From: liu.x... ＠ gmail.com <liu.xiaomo ＠ gmail.com>
Date: 2021年10月26日(火) 13:14
Subject: [aifin-worldwide] [2nd CFP]: The AAAI-22 Workshop on
Knowledge Discovery from Unstructured Data in Financial Services (KDF
‘22) - Deadline: 11/12/2021
To: AI in Finance Worldwide <aifin-worldwide ＠ googlegroups.com>


Description:

Knowledge discovery from various data sources has gained the attention
of many practitioners in recent decades. Its capabilities have
expanded from processing structured data (e.g. DB transactions) to
unstructured data (e.g. text, images, and videos). In spite of
substantial research focusing on discovery from news, web, and social
media data, its applications to datasets in professional settings such
as legal documents, financial filings, and government reports, still
present huge challenges. Possible reasons are that the precision and
recall requirements for extracted knowledge to be used in business
processes are fastidious, and signals gathered from these knowledge
discovery tasks are usually very sparse and thus the generation of
supervision signals is quite challenging.



In the financial services industry particularly, a large amount of
financial analysts’ work requires knowledge discovery and extraction
from different data sources, such as SEC filings, loan documents,
industry reports, etc., before they can conduct any analysis. This
manual extraction process is usually inefficient, error-prone, and
inconsistent. It is one of the key bottlenecks for financial services
companies to improve their operating productivity. These challenges
and issues call for robust artificial intelligence (AI) algorithms and
systems to help. The automated processing of unstructured data to
discover knowledge from complex financial documents requires a series
of techniques such as linguistic processing, semantic analysis, and
knowledge representation & reasoning. The design and implementation of
these AI techniques to meet financial business operations require a
joint effort between academia researchers and industry practitioners.



Furthermore, based on the reflection and feedback from our 2020 and
2021 AAAI KDF workshops, the 2022 workshop is particularly interested
in financial domain-specific representation learning, open financial
datasets and benchmarking, and transfer learning application on
financial data.





Topics:

We invite submissions of original contributions on methods, theories,
applications, and systems on artificial intelligence, machine
learning, natural language processing & understanding, big data,
statistical learning, data analytics, and deep learning, with a focus
on knowledge discovery in the financial services domain. The scope of
the workshop includes, but is not limited to, the following areas:

Representation learning, distributed representations learning and
encoding in natural language processing for financial documents;
Synthetic or genuine financial datasets and benchmarking baseline models;
Transfer learning application on financial data, knowledge
distillation as a method for compression of pre-trained models or
adaptation to financial datasets;
Search and question answering systems designed for financial corpora;
Named-entity disambiguation, recognition, relationship discovery,
ontology learning and extraction in financial documents;
Knowledge alignment and integration from heterogeneous data;
Using multi-modal data in knowledge discovery for financial applications;
AI assisted data tagging and labeling;
Data acquisition, augmentation, feature engineering, and analysis for
investment and risk management;
Automatic data extraction from financial fillings and quality verification;
Event discovery from alternative data and impact on organization equity price;
AI systems for relationship extraction and risk assessment from legal documents;
Accounting for Black-Swan events in knowledge discovery methods

Although textual data is prevalent in a large amount of
finance-related business problems, we also encourage submissions of
studies or applications pertinent to finance using other types of
unstructured data such as financial transactions, sensors, mobile
devices, satellites, social media, etc.

Submission:

All submissions must be original contributions and will be peer
reviewed, single-blinded. All the submissions must follow the AAAI-22
formatting guidelines, camera-ready style. We accept two types of
submissions - full research paper no longer than 8 pages (including
references) and short/poster/position paper with 2-4 pages.
Submissions will be accepted via EasyChair:
https://easychair.org/conferences/?conf=kdf22.





Workshop Organizing Committee:

Xiaomo Liu, J.P. Morgan Chase AI Research
Zhiqiang Ma, J.P. Morgan Chase AI Research
Armineh Nourbakhsh, J.P. Morgan Chase AI Research
Sameena Shah, J.P. Morgan Chase AI Research
Gerard de Melo, Hasso Plattner Institute
Le Song, Mohamed bin Zayed University of Artificial Intelligence



Workshop URL: https://aaai-kdf.github.io/kdf2022/



Important Dates:

Abstract Submission (optional): 11/05/2021
Paper Submission Deadline: 11/12/2021
Notification of Acceptance: 12/06/2021
Workshop Date: 2/28/2022 or 3/01/2022



We look forward to your participation. For general inquiries about
KDF, please write to inquiry.kdf2022 ＠ easychair.org.