An intelligent media data analytics framework with advanced analytics methods that collects, manages, analyzes and presents the social media data specifically serving the financial institutions requirements. It contains following modules: 1. Template based data collector to get social media data from different channels, such as news website, forums, facebook, twitter, etc; 2. Real time data acquisition, processing and storage; 3. Unified data repository for data storage, management and query; 4. Data search and query APIs make modelled data available to customer for additional analysis; 5. Advanced analytics algorithms for serving specific financial sector requirements using up-to-date NLP, machine learning, deep learning technologies Information extraction from complex text based on domain knowledge and context relevance Methods for users to develop their own domain-specific dictionaries Customizable media analytics modules: sentiment analysis, hot topic detection, etc. to support a variety of business needs 6. Configurable dashboard for serving different application requirements; 7. Integration test and customer site deployment; 8. Documentation (design, API, user manual). Contract service deliverables: 9 .a) Sentiment analysis for company product monitoring (CS1) ; 9. b) Hot topic detection for market trend catching (CS1) ; 9. c) Corporate news analysis for risk management (CS1); 9. d) Technical report on applying deep learning for risk assessment adjustment for the financial/ banking industry, which can be used to help more banks in future (attachment 8) (CS1)
AsiaPac Net Media Limited (Contract Service) [Sponsor]
AsiaPac Net Media Limited (Technical Licensing) [Sponsor]
Jin Peng Technology International Ltd [Sponsor]
Social media has become an important part for an organization’s business planning, affecting areas such as marketing, customer relation, risk monitoring etc. This project aims to deliver an end-to-end real time media data analytics platform, as well as several advanced analytics algorithms based on up-to-date NLP, machine learning, deep learning technologies to help companies better utilize media data to enhance their business operations.
The key features of the system include:
1. Flexible data collector that can be easily extended for new data sources;
2. Allow user to develop their own media data analytic capability;
3. Support different kinds of queries/analytics;
4. Domain-specific content analytics focusing on financial industry.