*****  To join INSNA, visit  *****

Apologies for cross-posting


Please consider submitting your work to the 1st ICPR workshop on Pattern
Recognition in Intelligent Financial Analysis and Risk Management, to be
held in conjunction with ICPR 2018 ( on the 20th
of August 2018 in Beijing, China.

Accepted papers (10 pages LNCS style, including references) will appear in
the ICPR Workshops LNCS proceedings published by Springer. Extended
versions of the best papers will be recommended for submission to a special
issue of the Pattern Recognition journal.

Submission Deadline: 15th May, 2018

For more information see the call for papers below and visit


In recent years, the financial industry has been a source of massive
volumes of both structured and unstructured data that is often unlabeled or
partially labeled, and where labels can be affected by noise and
uncertainty. Developing intelligent financial analysis and risk management
tools for such data presents major challenges for both practitioners and
academic researchers. This workshop mainly focuses on pattern recognition
and machine learning techniques such as kernel methods, feature selection,
reinforcement learning, deep learning, etc., for building intelligent
solutions for financial analysis and risk-based knowledge discovery.
Workshop topics include, but are not limited to:

- Financial time series analysis
- Modeling and simulation methods for financial risk with big data
- Portfolio optimization
- Risk management intelligence for internet finance
- Intelligent decision making in financial enterprise services
- Recommender systems for financial enterprises
- Individual credit scoring methods
- NLP methods for mining useful information from financial data
- Credit rating methods for institutional organizations
- Other artificial intelligence methods on financial analysis

Luca Rossi

Lecturer in Computer Science
School of Engineering and Applied Science
Aston University
Web: <>

SOCNET is a service of INSNA, the professional association for social
network researchers ( To unsubscribe, send
an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.