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Electronic theses and dissertations repository

 

Tesi etd-02132018-112759


Thesis type
Tesi di laurea magistrale
Author
ALLEBOUDY, AHMAD SHAREEF MOSTAFA KAMEL
email address
ahmad.alleboudy@outlook.com,ahmad.alleboudy@outlook.com
URN
etd-02132018-112759
Title
Deep learning for natural language processing of patent information
Struttura
INFORMATICA
Corso di studi
INFORMATICA
Commissione
relatore Bacciu, Davide
Parole chiave
  • Deep learning
  • ConvNets
  • IPC
  • Patent classification
Data inizio appello
02/03/2018;
Consultabilità
secretata d'ufficio
Data di rilascio
02/03/2088
Riassunto analitico
Machine learning is crucial for providing intelligent features to text analytics platforms. In this respect, deep learning techniques have gained increasing interest in the natural language processing community in the latter years. Nevertheless, consolidated statistical models are still robust, cheaper, faster and easy to apply than deep learning models. In this thesis, the problem of analyzing textual descriptions of patents is approached by a mixture of deep learning and statistical models for word embeddings and text classification, embedding them into the Mergeflow AG analytics platform
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