Time:
Wednesday, September 12, 2018 - 16:00 to 17:30
Talks
Analyzing diverse data from multiple sources evokes intelligence - the ability to acquire and apply knowledge and skills - and reasoning is of the skills we need to make sense of the world around us.
Milena Yankova
PhD.
Ontotext
https://ontotext.com/
Dr. Yankova-Doseva obtained a PhD in Computer Science from the University of Sheffield. Her thesis was on combining information and resolving identity issues coming from multiplicity and redundancy of information, a common problem that appears in the process of knowledge extraction from heterogeneous sources. Since joining Ontotext in 2004 (while it was still a lab within Sirma), Dr.
The Canadian Broadcasting Corporation (CBC) has evolved from using disparate systems for managing content and ontologies to focusing on data integration and quality management.
In addition to implementing technological improvements, CBC also focused on breaking down silos in order to socialize semantic concepts across the organization.
In this talk you will learn about CBC’s 18 month journey improving the management of content and ontologies through a comprehensive data strategy.
Kathryn Lee
Masters of Library and Information Studies
Canadian Broadcasting Corporation
http://www.cbc.ca/
Kathryn is responsible for data management at the Canadian Broadcasting Corporation. Her focus is on improving the quality of metadata and metadata flow between systems to enhance the discoverability of content and the ability to obtain more in depth business intelligence.
Stefan Piruzevski
MBA
Canadian Broadcasting Corporation
http://www.cbc.ca/
Stefan is CBC's product manager responsible for the tools content producers use to publish stories to the web. He places a heavy focus on supporting content production through data management. Stefan uses communication and collaboration strategies to drive product development among cross-functional teams.
Today’s market is flooded with Natural Language Processing (NLP) tools that allow for an easy extraction of sentiment information from raw text. Whereas these could be a good start to explore the kind of richness that sentiment analysis can bring to the table, much more is needed in order to do this at a level where real actionable insights come out of the raw data. Symanto has been building the most cutting edge AI technology for psychological profiling. We want to present at SEMANTiCS 2018 how we have harnessed deep learning technology to build an NLP engine capable of:
Marc Franco Salvador
PhD.
Symanto Research
https://www.symanto.net/
Marc Franco Salvador is a Principal Research Scientist at Symanto, a data analytics company based on psycholinguistic profiling and artificial intelligence. In this role, he works with his team to provide our data analytics platform with novel solutions based on the latest techniques of natural language processing, machine and deep learning.