Thesis etd-04172019-163152 |
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Thesis type
Tesi di dottorato di ricerca
Author
CHIARELLO, FILIPPO
URN
etd-04172019-163152
Thesis title
Mining Technical Knowledge
Academic discipline
ING-IND/35
Course of study
INGEGNERIA DELL'ENERGIA, DEI SISTEMI, DEL TERRITORIO E DELLE COSTRUZIONI
Supervisors
tutor Prof. Bonaccorsi, Andrea
relatore Prof. Fantoni, Gualtiero
relatore Prof. Fantoni, Gualtiero
Keywords
- Engineering Design
- Innovation
- Natural Language Processing
- Patent Mining
- Text Mining
Graduation session start date
30/04/2019
Availability
Full
Summary
The information field companies are living in has changed dramatically over the last years bringing a new challenge for management engineers. This discipline comes with engineering methodologies applied to inherent systems but, nowadays, activities with greater added value for companies are hardly standardized and non-repetitive. The enormous amount of information, which is changing the environment of companies, has a determinant impact on Research and Development, Design, Marketing and Human Resources Management: all functions with high strategic content, and so knowledge. Since documents written in natural language contains knowledge by design, management engineers has nowadays the great opportunity to exploit the technical knowledge hidden in this unstructured sources to generate value.
The aim of this thesis is to design methods and processes for the analysis of technical documents in order to extract valuable knowledge for companies. The methods are ensembles of Natural Language Processing and Managements Engineering techniques. The methods has the goal of providing correct knowledge exchange between humans and machines, leading to incorporate knowledge of the experts inside machine-learning systems and experts’ ability to use in their process of decision making inductively generated knowledge of machines.
The aim of this thesis is to design methods and processes for the analysis of technical documents in order to extract valuable knowledge for companies. The methods are ensembles of Natural Language Processing and Managements Engineering techniques. The methods has the goal of providing correct knowledge exchange between humans and machines, leading to incorporate knowledge of the experts inside machine-learning systems and experts’ ability to use in their process of decision making inductively generated knowledge of machines.
File
| Nome file | Dimensione |
|---|---|
| Mining_T...rello.pdf | 20.70 Mb |
| relazion...orato.pdf | 57.23 Kb |
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