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Injection of Knowledge in a Sourcing Recommender System
Molka Tounsi Dhouib, Catherine Faron, Andrea G. B. Tettamanzi

Injection of Knowledge in a Sourcing Recommender System

Science & Mathematics Published 2020 Verification Pending

Overview & Synopsis

Recommender systems provide suggestions to users for items that best meet their needs. In this work, we study the benefits of using knowledge and, more specifically, a 'bag of concepts' representation to enhance a recommender system in the sourcing domain. We tested our approach in a real-world case study provided by the Silex company. The experimental results show that injecting knowledge in the recommendation process outperforms word embedding approaches.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Injection of Knowledge in a Sourcing Recommender System
Author / Organization Molka Tounsi Dhouib, Catherine Faron, Andrea G. B. Tettamanzi
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2020
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-231493
Original Source Link Visit Source Page on hal.science »