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http://hdl.handle.net/10609/109546
Title: Predictions of new graph relationships - The Movie DataBase dataset
Author: Dolz Fernández, Jose Luis
Director: Casas Roma, Jordi
Tutor: Hernández González, Jerónimo
Keywords: graph analysis
relationship prediction
movies
Issue Date: 7-Jan-2020
Abstract: Thanks to the huge amount of data that is collected nowadays, models can be created to make all kinds of predictions. Graphs are a speci c type of model that can connect this data through relationships and predict new ones. A clear example is the suggestions of new people to connect with in social networks. In this project, the information contained in The Movie Database of almost 5000 films from 1916 to 2017 is used to make a graph model and to predict brand new relationships: which actors will work together, who will be the director of a new blockbuster, etc. These new predictions are created by using machine learning over the relationships. The results obtained with best prediction algorithm used show an accuracy of 60%. Hence, further work is needed to tweak features extraction out from the graph model to improve the precision of these relationship predictions.
Language: English
URI: http://hdl.handle.net/10609/109546
Appears in Collections:Bachelor thesis, research projects, etc.

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