USING RECOMMENDATION SYSTEM TO HELP STUDENTS CHOOSE A CAREER FIELD BASED ON THEIR INTERESTS
Abstract
Several researchers study Recommendation Systems to assist users in the retrieval of relevant goods and services, mostly used in e-commerce.
Several researchers study Recommendation Systems to assist users in the retrieval of relevant goods and services, mostly used in e-commerce.
However, there is limited information of the impact of Recommendation Systems in other domains like education. Thus, the objective of this study is to summarize the current knowledge that is available as regards Recommendation Systems that have been employed within the education domain to support educational practices.
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Robin Burke, Alexander Felfernig, Mehmet
H. Göker, Recommender Systems: An Overview, http://josquin.cs.depaul.edu/~rburke/pubs/burk e-etal-aimag11a.pdf
Recommender Systems the start of marketing personalization -
https://datasciencetips.com/recommender- systems-the-start-of-marketing- personalization/
Francesco Ricci and Lior Rokach and Bracha Shapira, Introduction to Recommender
Systems Handbook, Recommender Systems Handbook, Springer, 2011, pp. 1-35
Goldberg, D., Nichols, D., Oki, B.M., Terry, D.: Using collaborative filtering to weave an information tapestry. Commun. ACM 35(12), 61–70 (1992)
Pankaj Gupta, Ashish Goel, Jimmy Lin, Aneesh Sharma, Dong Wang, and Reza Bosagh Zadeh WTF:The who-to-follow system at Twitter, Proceedings of the 22nd international conference on World Wide Web
John S. Breese; David Heckerman & Carl Kadie (1998). Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence (UAI'98). arXiv:1301.7363.
D.H. Wang, Y.C. Liang, D.Xu, X.Y. Feng,
R.C. Guan(2018), "A content-based recommender system for computer science publications", Knowledge-Based Systems, 157: 1-9
Lakiotaki, K.; Matsatsinis; Tsoukias, A (March 2011). "Multicriteria User Modeling in Recommender Systems". IEEE Intelligent Systems. 26 (2): 64–76. CiteSeerX 10.1.1.476.6726. doi:10.1109/mis.2011.33.
Bouneffouf, Djallel (2013), DRARS, A Dynamic Risk-Aware Recommender System (Ph.D.), Institut National des Télécommunications
Flask Installation - https://flask.palletsprojects.com/en/1.1.x/instal lation/#install-flask
Flask Quickstart (Get started with a Simple Flask Project) - https://flask.palletsprojects.com/en/1.1.x/quick start/#a-minimal-application
DOI: https://doi.org/10.26483/ijarcs.v11i0.6602
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