Comparasion of recommender systems for stock inspiration
Recommender systems are apparent in our lives through multiple different ways, such asrecommending what items to purchase when online shopping, recommending movies towatch and recommending restaurants in your area. This thesis aims to apply the sametechniques of recommender systems on a new area, na...
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| Format: | Others |
| Language: | English |
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Linköpings universitet, Programvara och system
2021
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176408 |