Knowledge discovery, Visual Analytics and Innovation in Social Computing workshop
by Tallinn University of Technology
Based on Master’s Programme in Software Engineering and Cyber Security
Estonia is well known for its eagerness in embracing technology driven innovation. It is a pioneer in
electronic identity, electronic voting, and vigorous in adopting mobile technology, online banking and
electronic government services. Estonia is also home to internationally successful IT innovations as well
as a groundswell of IT ventures. The module will expose students to this exciting environment and give
them a glimpse into innovative and cutting-edge knowledge discovery, visual analytics and social
computing topics.
The workshop will be held during the 2 days, 6 academic hours on both days.
What will the participants gain?
Participants will gain an understanding of the importance of gathering, capturing, analyzing and making
sense of the data generated by us and surrounding us. This workshop will consist of six parts:
- Introduction to knowledge discovery, data mining and visual analytics;
- Fundamental concepts in making sense of the data: similarity, seriation and clustering;
- Combining data mining and information visualization methods for collaborative visual analytics;
- Social Network Analysis and how is it connected with data mining and visual analytics
disciplines;
- Understanding Social Data Revolution (socialdatarevolution.com) and its interplay with data
mining and social computing;
- Hands-on exercises to analyze the social computing data.
"Social Computing Research focuses on methods for harvesting the collective intelligence of groups of people in
order to realize greater value from the interaction between users and information. "
-- HP Social Computing Research (http://www.hpl.hp.com/research/idl/)
Participants of the workshop:
Students taking this module should have a desire to make sense of the vast amount of data around us
and have basic knowledge of computer programming and database systems. Practical experience in
software development or database systems would be desirable, but not essential. The course is highly
suitable for IT professionals, especially those working in industries, where a high number of customers
are being served (telecommunication, banking, retail etc.).
Max number of participants: 25
Background introductory material (articles, books, videos): http://data.ttu.ee/shanghai/
Instructors
Innar Liiv is an Associate Professor of Data Mining in the Department of Informatics at Tallinn University
of Technology. He is the Head of Industrial Data Mining Lab, which does joint research and training
projects with various companies from the industry (banking, telecommunication, supply chain
management, warehousing etc.) and teaches similar topics (data mining, business intelligence, customer
behavior analysis) to logistics, IT and business students. Having worked in software development,
advertising and publishing, he enjoys the research of customer analytics, gaining shopper insights and
understanding their behavior.
Ehitajate tee 5
19086 Tallinn ESTONIA
Phone +372 620 2002
Fax
+372 620 2020
ttu@ttu.ee
www.ttu.ee
2
Rain Öpik is an Assistant Lecturer in the Department of Informatics at Tallinn University of Technology.
He is doing research on data mining and teaches several courses connected to data warehouses,
enterprise resource planning, customer relationship management and information systems. Rain has
extensive hands-on experience from the supply chain management industry and has consulted several
clients on various business information system projects.
More information: Ms. Kätlin Keinast, Director of International Marketing and Admission, Tallinn
University of Technology, katlin.keinast@ttu.ee, -372 620 2022.