Personalised Recommendations and Profile Based Re-ranking Improve Distribution of Student Opportunities
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F23%3A00374425" target="_blank" >RIV/68407700:21240/23:00374425 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-42519-6_21" target="_blank" >https://doi.org/10.1007/978-3-031-42519-6_21</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-42519-6_21" target="_blank" >10.1007/978-3-031-42519-6_21</a>
Alternative languages
Result language
angličtina
Original language name
Personalised Recommendations and Profile Based Re-ranking Improve Distribution of Student Opportunities
Original language description
Modern technical universities help students get practical experience. They educate thousands of students and it is hard for them to connect individual students with relevant industry experts and opportunities. This article aims to solve this problem by designing a matchmaking procedure powered by a recommendation system, an ontology, and knowledge graphs. We suggest improving recommendations and reducing the cold-start problem with a re-ranking module based on student educational profiles for students who opt-in. Each student profile is represented as a knowledge graph derived from the successfully completed courses of the individual. The system was tested in an online experiment and demonstrated that recommendations based on student educational profiles and their interaction history significantly improve conversion rates over non-personalised offers.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023)
ISBN
978-3-031-42518-9
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
11
Pages from-to
217-227
Publisher name
Springer
Place of publication
Cham
Event location
Salamanca
Event date
Sep 5, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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