Thesis etd-04092020-120722 |
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Thesis type
Tesi di laurea magistrale
Author
OCCHIPINTI, DANIELA
URN
etd-04092020-120722
Thesis title
Industrial Strength Multilingual Named Entity Collection for the SPIRIT Project
Department
FILOLOGIA, LETTERATURA E LINGUISTICA
Course of study
INFORMATICA UMANISTICA
Supervisors
relatore Prof. Romani, Francesco
correlatore Dott. De Mattei, Lorenzo
controrelatore Prof.ssa Simi, Maria
correlatore Dott. De Mattei, Lorenzo
controrelatore Prof.ssa Simi, Maria
Keywords
- Deep Learning
- Microservices Architecture
- Named Entity Recognition
- Natural Language Processing
- Open Domain
- OSINT
Graduation session start date
27/04/2020
Availability
Withheld
Release date
27/04/2090
Summary
Scalable privacy preserving intelligence analysis for resolving identities (SPIRIT) is a Cybersecurity and OSINT project which has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 786993. The SPIRIT Project aims to provide an innovative platform based on an integrated approach for the multimodal and multilingual analysis of different types of content from different types of sources in order to facilitate cognitive tasks in the resolution of criminal identities. In the present work we give a detailed overview of the SPIRIT platform's architecture and pipelines, showing the entire technological stack. Then, we will shift the attention to the NLP and Deep Learning techniques adopted and the experiments conducted in order to provide a performing Multilingual Open Domain Named Entity Recognition engine.
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