Politecnico di Torino (logo)

NERD for NexGenTV

Lorenzo Canale

NERD for NexGenTV.

Rel. Laura Farinetti. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Del Cinema E Dei Mezzi Di Comunicazione, 2018

PDF (Tesi_di_laurea) - Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives.

Download (4MB) | Preview

My graduation thesis “NERD for NexGenTV” documents the contribution I gave to the NexGenTV project during my internship at Graduate school and research centre EURECOM. The project aims to enrich the experience of the television viewer on a support device, enriching the TV transmissions with complementary information. My thesis focuses on two NexGenTV subtasks: Named Entity Recognition (NER) and Named Entity Disambiguation (NED): the final goal was to automatically detect, recognize and link all spottable named entity presented in a corpus of subtitle transcripts of French political debates. My work presents two multilingual ensemble methods that combine the responses of web services NER and NED in order to improve the quality of the predicted entities. Both methods represent the information got by the extractor responses as real-valued vector (features engineering) and use Deep Neural Networks to produce the final output.

Relators: Laura Farinetti
Academic year: 2017/18
Publication type: Electronic
Number of Pages: 92
Corso di laurea: Corso di laurea magistrale in Ingegneria Del Cinema E Dei Mezzi Di Comunicazione
Classe di laurea: New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING
Ente in cotutela: EURECOM - Telecom Paris Tech (FRANCIA)
Aziende collaboratrici: Eurecom
URI: http://webthesis.biblio.polito.it/id/eprint/7601
Modify record (reserved for operators) Modify record (reserved for operators)