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A Model for Recommending Specialization Courses Based on the Professional Profile of Candidates

Authors:
Antonio Souza
Sandra Stump

Keywords: recommender systems; data mining; data filtering techniques; academic counselling

Abstract:
The paper studies the candidates’ professional profile on choosing a specialization course. A methodology based on the processes Knowledge Discovery in Databases (KDD) and CRoss-Industry Standard Process for Data Mining (CRISP-DM) is applied, and proposed a course recommendation model, using a technique of data mining based on decision trees for the discovery of relevant knowledge from database, which will identify the most suitable course to a candidate's profile. In this study, it is expected to be detected the specialization courses which best suits each candidate profile, giving support to academic institution to satisfy candidates needs and reduce the number of dropouts or changes.

Pages: 155 to 159

Copyright: Copyright (c) IARIA, 2013

Publication date: February 24, 2013

Published in: conference

ISSN: 2308-4375

ISBN: 978-1-61208-254-7

Location: Nice, France

Dates: from February 24, 2013 to March 1, 2013