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
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
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
Name of the periodical
Lecture Notes in Networks and Systems
ISSN
2367-3370
e-ISSN
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Volume of the periodical
2023
Issue of the periodical within the volume
748
Country of publishing house
CH - SWITZERLAND
Number of pages
11
Pages from-to
217-227
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85171436276