MULTISENSOR – Mining and Understanding of multilinguaL contenT for Intelligent Sentiment Enriched coNtext and Social Oriented inteRpretation
Start 2013.11.01, Finish 2016.10.30
MULTISENSOR is an EU funded research project, which aims at advancing the research and development of multilingual media analysis technologies.
Contact: Boyan Simeonov
The goal is to enable users (e.g. journalists, entrepreneurs) to attain a comprehensive and exact understanding of topics they are engaged in, not only from their own but from multiple viewpoints.
Scanning multiple heterogeneous sources, MULTISENSOR helps to gather and semantically integrate various local subjective and biased views disseminated via TV, radio, mass media websites and social media.
Using sentiment, social and spatiotemporal methods, MULTISENSOR then helps to interpret, relate and summarize economic information and news items.
Ontotext’s role includes Semantic Reasoning and Decision Support, and data engineering for Linguistic Linked Data. More specifically, our tasks include:
- To provide the infrastructure which will serve as the storage layer for the (meta)data of the MULTISENSOR platform
- To develop reasoning techniques beyond state of the art allowing for efficient information selection from heterogeneous data pools, e.g. hybrid reasoning, multi-threaded reasoning, temporal reasoning, geo-spatial reasoning
- To produce a decision support mechanism based on the developed reasoning techniques, listed above, and on cognitive techniques for context aware graph navigation, such as spreading activation.
- Knowledge modelling to identify and select the most appropriate ontologies that can fulfil the demand for unambiguous communication and information sharing relevant to MULTISENSOR and driven by the use cases, and extend with appropriate ontologies