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Bachelor thesis

Publication date

2016-01-28

Publication license

memòria: cc-by-nc-sa (c) Álvaro Parafita Martínez, 2016
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/97486

News similarity with natural language processing

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Abstract

News articles are pieces of Natural Language that comply with the model of 5W1H, meaning, they should answer to the following six questions: What, Who, Where, When, Why and How. This project takes advantage of that assumption to create an algorithm capable of building a representation of a news article and a distance between such representations for any pair of politics news. With that knowledge, a global dis- tance between entries based on similarity of content is built. That algorithm is assessed in comparison with the topic modeling algorithm Latent Dirichlet Allocation (LDA). Applications of the system with their corresponding visualisations are presented too.

Description

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2016, Director: Jordi Vitrià i Marca

Subject

Tractament del llenguatge natural (Informàtica), Intel·ligència artificial, Programari, Treballs de fi de grau, Algorismes computacionals, Python (Llenguatge de programació)

Subject (English)

Natural language processing (Computer science), Artificial intelligence, Computer software, Bachelor's theses, Computer algorithms, Python (Computer program language)

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Treballs Finals de Grau (TFG) - Enginyeria Informàtica
Programari - Treballs de l'alumnat

Citation

PARAFITA MARTÍNEZ, Álvaro. News similarity with natural language processing. [consulted: 15 of August of 2026]. Available at: https://hdl.handle.net/2445/97486

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