PROFIT: Raising Financial Awareness With Semantics

Schematic representation of data as bubbles with connecting lines

PROFIT: Raising Financial Awareness With Semantics

The European project consortium develops a financial awareness platform that will be publicly available. The smart application shall improve the financial literacy of various user groups ranging from teenagers, mid-career professionals to retirees. The available education services and finance news will be dynamically adapted to the user behaviour.

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“72% agree they ‘understand the importance of personalisation, but don’t know how to do it’.
— Econsultancy (2013)

How Does the Financial Awareness Platform Work?

The platform will provide adaptable financial education learning resources. Depending on the user's progress and interests, the learning material and finance news will adapt. For the finance news, publicly available resources will be aggregated, semantically analysed and reused in the appropriate context. The application functionality strongly relies on user engagement. The underlying machine-learning algorithms incrementally improve through the user interaction that is stimulated through various gamification approaches. Users are also encouraged to customize their financial news aggregator by adding or removing concepts and topic relations in the underlying knowledge model of the application. Involving users actively in adapting the knowledge model is possible due to the smooth user interface of the PoolParty taxonomy management module. It marks an innovative approach on how to provide user control over cognitive applications.

Which Linked Data Technologies Enable the Dynamic Platform?

A knowledge graph is at the core of the dynamic application. It is the basis for the text analytics of the aggregated news and personalized display of content. Various available Natural Language Processing methods have to be adapted and improved for the text mining tasks: Text categorization, text readability, sentiment analysis and  sentence boundary disambiguation techniques detect which aggregated data is context-relevant for the application services.

Further Developments at Semantic Web Company

The data processing of the financial awareness platform is executed with the PoolParty module UnifiedViews. Newly developed algorithms for better sentiment analysis and text categorization are directly reused for the text mining component PoolParty Extractor. The heterogeneity of the aggregated data brings the technical capacity of the PoolParty module to a new level.

Project title

PROFIT

Project website

http://projectprofit.eu/

Duration

3 years

Methods Applied

  • Sentiment Analysis
  • Wordsense disambiguation
  • Personalization

Project sponsors

LOD2: The Linked Data Technology Stack for Enterprises
PROFIT has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under grant agreement no 687895.

Lexicography Project

Incorporating lexicographical data into knowledge graphs helps to solve language ambiguity challenges.

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