Session Information

Understanding Text with Deep Machine Learning

Speaker(s):

Sebastian Arnold (Beuth University of Applied Sciences Berlin)
Prof. Dr. Alexander Löser (Beuth University of Applied Sciences Berlin)
Back to last page:
 
A large number of people in the gaming community use written language to express sentiments and facts about players, walk-troughs, hints and new games. However, reading this text using machines and learn about gamers' demands is a difficult problem. In our talk we present deep machine learning techniques for understanding these semantics. For example, we introduce the DATEXIS Adaptive Entity Linking project where we utilize neural networks to extract structured data from domain-specific texts. We also demonstrate our research prototypes for market research, such as extraction-as-you-type, interactive review analysis and automatic generation of rare domain dictionaries. Finally, we give some insights into the scientific background and nuts and bolts we discovered when executing these algorithms efficiently on CUDA graphic cards.
Audience adressed: 
TBA
Takeaway: 

TBA

Session Type: 
Talk
Track: 
Code / Platforms / Tools
Experience level adressed: 
Intermediate
Time slot: 
2016-04-19 17:00
Room: 
Channel 5

Event Sponsors

Sponsor Partners

No sponsors in this category have been announced yet.

Media and Partners