Abstract
Semantics is a well-kept secret in texts, accessible only to humans. Artificial Intelligence struggles to enrich machines with human-like features, therefore accessing this treasure and sharing it with computers is one of the main challenges that the computational linguistics domain faces nowadays. In order to teach computers to understand humans, language models need to be specified and created from human knowledge. While still far from completely decoding hidden messages in political speeches, computer scientists and linguists have joined efforts in making the language easier to be understood by machines. This paper aims to introduce the VoxPopuli platform, an instrument to collect user generated content, to analyze it and to generate a map of semantically-related concepts by capturing crowd intelligence.
Paper Type
Event
Mining Social Media to Extract Structured Knowledge through Semantic Roles
Semantics is a well-kept secret in texts, accessible only to humans. Artificial Intelligence struggles to enrich machines with human-like features, therefore accessing this treasure and sharing it with computers is one of the main challenges that the computational linguistics domain faces nowadays. In order to teach computers to understand humans, language models need to be specified and created from human knowledge. While still far from completely decoding hidden messages in political speeches, computer scientists and linguists have joined efforts in making the language easier to be understood by machines. This paper aims to introduce the VoxPopuli platform, an instrument to collect user generated content, to analyze it and to generate a map of semantically-related concepts by capturing crowd intelligence.
Recommended Citation
Trandabat, D., Gifu, D., & Cristea, D. (2017). Mining Social Media to Extract Structured Knowledge through Semantic Roles. In Paspallis, N., Raspopoulos, M. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development: Advances in Methods, Tools and Management (ISD2017 Proceedings). Larnaca, Cyprus: University of Central Lancashire Cyprus. ISBN: 978-9963-2288-3-6. http://aisel.aisnet.org/isd2014/proceedings2017/CogScience/5.