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Title:
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ORIEB, A CRS FOR ACADEMIC ORIENTATION USING QUALITATIVE ASSESSMENTS |
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Author(s):
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Emilio J. Castellano , Luis Martínez |
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ISBN:
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978-972-8924-58-4 |
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Editors:
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Miguel Baptista Nunes and Maggie McPherson (series editors: Piet Kommers, Pedro Isaías and Nian-Shing Chen) |
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Year:
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2008 |
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Edition:
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V II, 2 |
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Keywords:
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Academic Collaborative Recommender System, Qualitative Information. |
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Type:
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Short Paper |
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First Page:
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38 |
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Last Page:
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42 |
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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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Collaborative Recommender Systems (CRS) are very useful tools that help people to select items in a huge search space,
based on the idea that people with similar taste of preferences in an topic make similar decisions concerning to that topic.
There are many commercial applications that show the utility of these systems. In this contribution we shall introduce
OrieB, a CRS working in the Academic Orientation domain in order to support advisors helping students of secondary
school to make decisions about their academic future. OrieB will use students marks as input data in order to suggest
their academic possibilities by providing qualitative recommendations based on the fuzzy linguistic approach. |
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