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. n 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 reflections and feedbacks 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.

This workshop will focus on research into the use of AI techniques to extract knowledge from unstructured data in financial services. The program of the workshop will include invited talks, and spotlight paper presentations, to showcase research opportunities, novel solutions and systems, success stories, and future directions. We cordially welcome researchers, practitioners, and students from academic and industrial communities who are interested in the topics to participate and/or submit their original work. The topics and submission requirements can be found in call for papers.


For registration, please use the AAAI-22 registration website.

Important Dates (Anywhere on Earth)

Abstract Submission (optional) Friday Nov 5, 2021
Paper Submission Deadline Saturday Nov 12, 2021
Nov 20, 2021
Notification of Acceptance Friday Dec 6, 2021
AAAI-22 Early Registration Deadline Friday Dec 31, 2021
Workshop Tue March 1, 2022

Contact Information

We look forward to seeing you in KDF 2022! For general inquiries about KDF, please write to