In collaboration with EIT Digital, this workshop will be focused on Big Data.

Two experts, Cem Kubilay from Microsoft and Ville Ollikainen from VTT, will share their knowledge and expertise on big data, analytics and privacy. You will have the chance to get  insights on the topic and answers to your questions.

The workshop will be held in English.

 

Agenda:

14:00-16:00 “Modernization of Data Management”

-Cem Kubilay, Emerging Technologies – Business Development Manager CEE, Microsoft Turkey & Israel

Data management and analytics is getting more interest from businesses every year. Besides the variety of data types and data sources, traditional analytics are changing as well. It is also important to adapt business to the new analytics which will help companies to gain competitive advantage.

 

16:00-18:00 “Is there a need for an anonymous recommendation network?”

-Ville Ollikainen, Senior Scientist, VTT Technical Research Centre of Finland

During the past decade media industry has gone – and is still going – through a fundamental change. Advertising to target groups or demographics is rapidly becoming obsolete. On the other hand, number of sources where to get content has exploded. All this fragmentation is leading to a number of questions, for instance how to find content and how to efficiently target advertising. A major challenge in recommendation systems is that they are either domain specific or need substantial amount of data. By ingesting both user data and item data and increasing  performance by creating in-depth user profiles, question of ownership to a substantial amount of private and business sensitive data, arises. In this session an approach called UPCV (Ubiquitous Personal Context Vectors) is presented as an example of a networked recommendation engine technology which respects privacy.

In addition to the presentation this session will discuss related topics, such as:

  • What other alternatives do we have for the current model of a few global players?
  • What are the relations between privacy and quality of recommendations?
  • What could be value propositions for a recommendation network where all parties
  • can control their own data?
  • How to build trust in such a network?
  • Eventually, who would be interested?