A Web-Based Prototype Course Recommender System using Apache Mahout

by Nkongolo, Mike
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Nkongolo, Mike A Web-Based Prototype Course Recommender System using Apache Mahout
Nkongolo, Mike - A Web-Based Prototype Course Recommender System using Apache Mahout

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Description


Project Report from the year 2017 in the subject Computer Science - Miscellaneous, grade: BSc Honours in Computer Science, , course: Honors research project, language: English, abstract: Most universities offer a wide range of courses in which students can enrol. As a result, students may feel overwhelmed with the many possibilities and large amount of information, resulting in having a difficult time deciding what to sign up for. To this end, there is a need for a system that can assist students in this crucial process. Thus, we set out to develop a web-based recommender application that could generate a list of valuable, accurate course recommendations, taking into account a student's likelihood of succeeding academically.

Choosing an effective and stimulating set of courses is not an easy task for a student. There are several factors at play when it comes to choosing courses that one must study. One of these factors may be the assumed difficulty of a course that a student is considering to take. Of course, if the course is compulsory, then the student has no choice but to enrol in it. However, in the situation in where there are many different subjects to choose from, the student may shy away from taking optional courses that might pose a significant challenge, in terms of workload or being unable to fully understand the course content. These courses would clearly have a negative effect on academic performance. However, there may also be some students who are looking to be challenged, and for whom choosing more difficult courses would be an exciting challenge. In terms of academic performance, effective course selection is of utmost importance in ensuring a student is able to succeed in her or his studies and obtain their qualification(s).

Contributors

Author:
Nkongolo, Mike

Further information

Media Type:
Taschenbuch
Publisher:
GRIN Verlag
Biography Artist:

Mike Nkongolo received the BSc (Hons) degree in computer science from the University of the Witwatersrand, Johannesburg, South Africa, in 2016. He is currently working toward the Masters degree in the School of Computer Science and Applied Mathematics, University of the Witwatersand. His research interests include the theory and applications of Intelligent Systems, Web-based platforms and Machine Learning, Sentiment detection in Web Mining, and Artificial Intelligence/Natural Languages Processing.
Language:
Englisch
Number of Pages:
96

Master Data

Product Type:
Paperback book
Release date:
24 October 2017
Package Dimensions:
0.21 x 0.148 x 0.006 m; 0.136 kg
GTIN:
09783668554368
DUIN:
1JORMOBT5AP
£52.49
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