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Title:
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MODELLING THE ENROLMENT ESERVICE OF A UNIVERSITY USING MACHINE LEARNING TECHNIQUES |
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Author(s):
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Ainhoa Yera, Iñigo Perona, Olatz Arbelaitz and Javier Muguerza |
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ISBN:
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978-989-8533-75-3 |
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Editors:
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Piet Kommers and Pedro Isaías |
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Year:
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2018 |
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Edition:
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Single |
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Keywords:
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eGovernment, eSociety, eServices, Web Usage Mining, Navigation Models |
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Type:
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Full Paper |
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First Page:
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83 |
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Last Page:
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91 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This work analyses the navigation in the enrolment eService of the University of the Basque Country. A complete data mining process shows that successful and failure navigation behaviours can be automatically modelled using data mining techniques. On the one hand, unsupervised machine learning techniques have shown that both aspects, where the users navigate and how they do it, affect to the success or failure of a navigation session. In both cases, the sessions in clusters labelled as success or failure, have more than 80% probability of being of that type. Besides, using supervised learning we are able to automatically distinguish the two navigation types with an accuracy rate of 98 % and to identify their main characteristics. Thus, we think that this research is a suitable basis to improve the eService analysed in a near future. |
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