Knowledge discovery from various data sources has gained the attention of many practitioners over the past 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 application to data 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, in particular, 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 the analysts 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 in improving 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 and reasoning. The design and implementation of these AI techniques to meet financial business operations requires a joint effort between academia researchers and industry practitioners.
This one-day virtual 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, spotlight paper presentations, and lightning poster 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-21 registration website.
Important Dates (Anywhere on Earth)
|Abstract Submission (optional)
|Paper Submission Deadline (Extended)
|Notification of Acceptance
|AAAI-21 Early Registration Deadline
|Feb 9, 2021
We look forward to seeing you in KDF 2021! For general inquiries about KDF, please write to email@example.com.